Machine Learning Science

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds in machine learning, artificial intelligence and related fields.Amazon scientists employ the company's working backwards method to identify problems to solve on behalf of customers in research areas ranging from machine learning to operations, GenAI, robotics, quantum computing, computer vision, economics, search, sustainability and more.Learn more about Amazon Science here: https://www.amazon.science/We are hiring across multiple businesses and in many locations across the US. Apply here to learn more about open roles that could be a compelling fit for your background. Key job responsibilitiesYou will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).BASIC QUALIFICATIONS- 10+ years minimum of hands-on science application experience- PhD in a relevant technical field (or equivalent experience in some cases) ...

Are you seeking an environment where you can drive innovation? Do you want to apply inference, advanced statistical modeling and techniques to solve world's most challenging problems in? Do you want to play a crucial role in the future of Amazon's Retail business? Do you want to be a part of a journey that develops a new technology from scratch for answering critical business question in Amazon Retail?Every time an Amazon customer makes a purchase, a number of systems are involved: these systems help optimize acquisition, enable a number of purchase options, ensure great , store products so they are available for fast delivery, and minimize package frustration. The Technology (SCOT) Group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it.The SCOT Lab team within SCOT Forecasting is responsible for designing and executing the inference and experimentation systems that measure the impact of SCOT initiatives. We are looking for senior applied scientists to drive innovation in SCOT by developing/building a new scientific approach and pushing our system further upstream in the innovation process. Key responsibilities of a Research Scientist in IPC Lab include: - Developing new statistical, causal, and machine learning techniques and develop solution prototypes to drive innovation - Working with technical and non-technical customers to design experiments and communicate results - Collaborating with our dedicated software team to create production implementations for large-scale data analysis - Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business - Presenting research results to our internal research community - Leading training and informational sessions on our science and capabilities - Your contributions will be seen and recognized broadly within Amazon, contributing to the Amazon research corpus and patent portfolio.To help describe some of our challenges, we created a short video about at Amazon - http://bit.ly/amazon-scotAmazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / AgeBASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The Rufus team is building foundational LLMs for Amazon Stores that fuse general world knowledge with Amazon e-commerce domain knowledge, to provide new and improved shopping experiences for our customers. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!BASIC QUALIFICATIONS- 2+ years of building machine learning models for business application experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in any of the following areas: Natural Language Processing (NLP), vision-language modeling, recommendation systems, web data processing, Large Language Models (LLM), or parallel and distributed computing ...

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!Key job responsibilitiesWe seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.The Sponsored Brands Advertiser Control team is a versatile environment, with a wide variety of challenges. We guide advertisers to make informed decisions by sharing insights and forecasts. We help advertisers deliver effective campaigns automatically by optimizing bids and targets on behalf of them. We enable advertisers to achieve brand advertising goals with maximum efficiency. We look at mega size data from both retail and advertising space, and coming up with ML and DL based science solutions through multiple products. In this role you will: - Research and build innovative machine learning and deep learning models utilizing the latest technologies such as LLM to provide personalized targeting, real-time forecasting and simplify campaign creation and management- Develop optimization solutions to automate bidding , targeting and budgeting on behalf of advertisers - Perform hands-on big data analysis and modeling to develop insights that increase advertiser monetization and merchandise sales without compromising shopper experience. - Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Write production code to bring models into production. - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Work with scientists and economists to model the interaction between organic sales and sponsored content and to further evolve Amazon's marketplace.Why you love this opportunity Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us BASIC QUALIFICATIONS- PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience- 5+ years of building models for business application experience- Experience programming in Java, C++, Python or related language ...

Amazon is among the top 10 most-visited website worldwide. Amazon's search experience is central to how hundreds of millions of customers shop using billions of queries to find products for sale. The scale and impact of Amazon Search is huge.Within the Amazon Search organization, the MIDAS (Metrics, Insights, Data Annotation for Search) team delivers high quality labeled data at scale in order to improve the search experience for shopping on Amazon through AI model training and evaluation as well as to produce metrics that measure our customer experiences. We focus on agility, linguistic expertise, high standards for data integrity, enabling self-service, and frugality of resources in order to meet or exceed our customers' expectations. We collaborate closely with several machine learning (ML) applied science, engineering, and product teams that develop and test ML models to improve the quality of semantic matching, ranking, computer vision, image processing, and augmented reality.The Language Engineer role in the MIDAS team owns the creation of the data annotation workflow, writing intuitive and labeler-friendly annotation guidelines, data wrangling and analysis, specifications for labeling UI templates, and reporting of labeled data quality metrics to deliver on internal customers' requirements and achieve the desired Amazon customer outcomes. In order to achieve high rates of accuracy and consistency in labeled data outputs, Language Engineers apply linguistic (i.e., semantics, syntax, pragmatics) and scripting expertise to overcome natural language processing and language understanding challenges.Key job responsibilities* Design and develop data annotation guidelines and workflows.* Manage and process large amounts of structured and unstructured data.* Adopt and design quality control metrics and methodology to evaluate the quality of data annotation.* Maximize productivity, process efficiency and quality through streamlined workflows, process standardization, documentation, audits and investigations on a periodic basis.* Handle annotation & data investigation requests from multiple stakeholders with high efficiency and quality in a fast-paced environment.* Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and workflows.* Initiate and contribute towards improvement projects, present solution proposals, and implement them.* Establish processes and mechanisms to onboard and train junior data associates on an ongoing basis.* Handle work prioritization and deliver based on business priorities.* Be flexible in changes to conventions deployed in response to customers’ requests and change workflows accordingly.BASIC QUALIFICATIONS* Bachelor’s or Master’s Degree in Linguistics, Computational Linguistics, Natural Language Processing (NLP), or other related field.* Relevant work experience of 5+ years.* Proficient in Python.* Knowledge of Regex, SQL, MS Excel, Git.* Ability to navigate a Unix terminal and use common command line tools.* Familiarity with annotation tools and workflows.* Excellent communication and strong organizational skills with a keen eye for details.* Comfortable working in a fast-paced, collaborative, and dynamic work environment.* Willingness to support several projects at one time and to accept reprioritization as necessary. ...

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk?Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes?If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group.Key job responsibilitiesThe scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.BASIC QUALIFICATIONS- 4+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize leading-edge engineering and science technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational, multi-turn interfaces. We also empower advertisers to reach shoppers, using their own voice to explain and demonstrate how their products meet shoppers' needs. We collaborate with various teams across multiple Amazon organizations to push the boundary of what's possible in these fields.We are seeking a science leader for our team within Sponsored Products & Brands organization. You'll be working with talented scientists, engineers, and technical program managers to innovate on behalf of our customers. An ideal candidate is able to navigate through ambiguous requirements, working with various partner teams and SDEs and have experience in Natural Language Processing, Ads recommendation systems, information/evidence retrieval and/or LLM prompt engineering. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!We are open to hiring candidates to work out of one of the following locations:Seattle, WA and New-York, NYKey job responsibilities- Serve as the Science lead in defining the Science charter for the team (for an entirely new space using LLMs) & leading other AS on the team- Build POCs, experiment, optimize and deploy models into production- Partner with other Science teams within the org to deliver features for a net new shopper experience - Run experiments/weblabs and be able to perform statistical analysis- Mentor other scientists on the team- Partnering with Principal PMT and SDM to influence the Product strategyNice to have - Experience in Ads recommendations & information / evidence retrieval - Experience working with Large Language Models & Prompt EngineeringBASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

AWS Support is looking for a high caliber Applied Scientist to build AI/GenAI experiences and foundations for Kumo Intelligent Tooling — the organization that owns products and services used by 10,000+ AWS Support staff to help 40,000+ unique monthly AWS customers, and is responsible for AWS Support’s strategic initiative to transform its business and delivery model through GenAI.We are looking for a Principal Scientist to join us and spearhead the AI revolution through intelligent solutions that assist customers and Support staff to troubleshoot and resolve technical issues. You are a hands-on contributor and will apply your knowledge to propose solutions, create software prototypes, and productize prototypes into production systems using modern software development tools and methodologies. In addition, you will support and scale your solutions to meet ever-growing customer needs use cases. You have strong verbal and written communication skills, are self-driven and deliver high quality results in a fast-paced environment.You will play a pivotal role in shaping the definition, vision, design, roadmap and development of solutions from beginning to end for hard, previously unsolved problems.Key job responsibilities- Lead and conduct advanced research in Large Language Models (LLMs), GenAI, and Deep Learning, with a focus on developing novel algorithms, architectures, and methodologies for technical support.- Stay up-to-date with the latest advancements in AI, LLMs, and GenAI, and identify opportunities to leverage cutting-edge technologies to deliver new Support offerings and capabilities to AWS customers.- Lead by example, demonstrating technical excellence that other scientists aspire to follow, fostering a culture of innovation and knowledge sharing, and taking time to mentor and develop team members- Collaborate with cross-functional teams, including scientists, engineers, and product managers, to translate research findings into practical applications.- Partner across AWS AI/GenAI service teams to influence and drive investment prioritization and product direction.- Evangelize our AI/GenAI innovations, results, and impact to customers, partners, and AWS senior leaders.About the teamKumo is the global product and engineering organization for AWS Support, a multi-billion $ business. Our mission is to empower innovators to get the most out of cloud services. We build technology that reimagines how people and automation combine to solve problems, remove risks, build with excellence, and drive business impact. We own critical cloud services used by all AWS customers to build, optimize, and operate at scale, including AWS Health, Trusted Advisor, Well-Architected, re:Post, Support Center, and AWS Managed Services. We also own services that enable AWS support teams to provide mission-critical, customer-obsessed support to our customers, including Command Center (the console platform for 14,000 frontline staff and technical account managers), Kumo Case Management (the contact center platform for technical support), Tool Contribution (the platform for support staff to build and reuse troubleshooting tools), and Business Case Authorization (the service for controlling access to customer metadata based on business justifications). AWS Kumo is a dynamic, agile, and collaborative team of individuals with diverse backgrounds, located around the globe with larger teams in the U.S., Canada, and South Africa.BASIC QUALIFICATIONS- Graduate degree (MS or PhD) in Computer Science, Machine Learning, Computational Linguistics, or a related field, with a strong focus on Natural Language Processing, Large Language Models, and Generative AI.- 7+ years of experience in AI and Machine Learning in industry.- Proven experience with a track record of thought leadership and contributions that have advanced business and customer results through AI. - Strong record of delivery in industry and ability to handle multiple competing priorities in a fast-paced environment. - Excellent written and verbal communication skills. ...

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time.Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking Manager Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your team and tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems. The position is located at Bellevue, WA, just next to Seattle with beautiful outdoors and great city life.Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilitiesAs a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include:* Lead a team of research and applied scientists towards design, development and evaluation of highly innovative ML models for solving complex business problems. * Technically lead and mentor the scientists on the team.* Research and apply the latest ML techniques and best practices from both academia and industry. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.A day in the lifeIn this critical role, you will be a technical leader in operations research or machine learning with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's supply chain globally. As a science manager on the team, you will engage in all facets of the process from ideation, business analysis and scientific research to development and deployment of advanced models. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their team, and their career.About the teamFulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.BASIC QUALIFICATIONS- Ph.D. in Computer Science, Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics, or a related field- 5+ years of hands-on experience in building machine learning models in business environment- Proven track in leading and mentoring scientists with demonstrated ability to serve as a technical lead- Strong fundamentals in problem solving, algorithm design and complexity analysis- Excellent communication skills, both written and oral catered appropriately towards both technical and business people.- Demonstrated ability to document the models and analysis and present the results/conclusions in order to influence business critical decisions ...

Interested in helping build Prime's content and offer experimentation system to drive huge business impact on millions of customers? Join our team of Scientists and Engineers developing algorithms to adaptively generate and experiment on new content, personalize, and optimize the customer experience with Amazon Prime. This includes identifying who our customers are and providing them with personalized relevant content. As an ML lead, you will partner directly with product owners to intake, build, and directly apply your modeling solutions.There are numerous scientific and technical challenges you will get to tackle in this role, such as adaptive experimentation, structured multi-armed bandits and its application to various types of experimentation and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from LLM's, Gen AI, deep learning, multi-armed bandits, optimization, and RL.As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLM's), and statistical modeling techniques.Major responsibilities - Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage Bandits and Reinforcement Learning for Experimentation and Optimization Systems. - Develop offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers.Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis.You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially with computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team. As an Applied Scientist on this team, you will:* Drive end-to-end GenAI projects that have a high degree of ambiguity, scale and complexity.* Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.* Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.* Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.* Identify and action data collection and labelling in conjunction with team members.* Research new and innovative machine learning approaches.* Present results and explain methods to senior leadership.Why you will love this opportunityAmazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Key job responsibilitiesThis role is focused on computer vision, latent diffusion models, and the related foundational models to produce generative imagery and videos. You will develop core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work. A day in the lifeOn a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership.About the teamThe team consists of applied scientists and machine learning engineers. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads.BASIC QUALIFICATIONS- 3+ years of building ML models- PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience- Experience programming in Python or C++ or a related language- Experience with GenAI model training and tuning ...

About Amazon Advertising:Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.About our team:Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods.Key job responsibilitiesWe are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning using LLMs. We also have some ongoing and highly leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for a seasoned Applied Science leader to build and deliver cutting-edge science and engineering solutions to improve our Stores business. In this role, you will lead a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing the scientific models, benchmarks, and services. Graduate education and hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a must. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity.Key job responsibilitiesKnowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.BASIC QUALIFICATIONS10+ years of building machine learning models for business application experiencePhD, or Master's degree and 10+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learning ...

Amazon's Next Generation Developer Experience (NGDE) Organization is looking for world class scientists and engineers to join its team to work on AI4Code, LLM, and natural language processing. This group is entrusted with developing core algorithms/capabilities for Amazon Q Developer. At NGDE's science team you will invent, implement, and deploy state of the art AI algorithms and systems for developers. You will build prototypes and explore conceptually new large scale AI solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.About the teamAWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS?Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Mentorship & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid WorkWe value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.BASIC QUALIFICATIONS- PhD, or Master's degree and 6+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon has the world’s most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. A core part of the operations is forecasting: We forecast the demand of hundreds of millions of products up to a year into the future. The forecasts are used to automatically order hundreds of millions worth of inventory weekly, decide where to place that inventory, and to establish labor plans for hundreds of warehouses.The Applied Scientist II will work with the Supply Chain Optimization Technologies (SCOT) Forecasting team and both business and engineering stakeholders worldwide to develop state of art machine learning models to forecast inbound shipment. The scientist develops novel algorithmic architectures, toward the ultimate goal of accurately predicting when and how Amazon receives shipments of millions of products world-wide. This drives down costs and enables the offer of lower prices and better in-stock selection for our customers.Working collaboratively, you will develop solutions to complex problems, such as designing the next generation of algorithms. As an Applied Scientist, you will continue to contribute to the research community, by working with other scientists across Amazon, as well as collaborating with academic researchers and publishing papers. Within SCOT Forecasting, our Science community values teamwork and recognizes the need to take chances and try new ideas that may fail. Furthermore, our builder culture means that Scientists and Software Development Engineers work closely together to invent and construct at a massive scale. Your work can be part of Amazon production system and result in concrete business impact. Key job responsibilities- Design, implement, and evaluate innovative models, agents, and software prototypes.- Collaborate with a team of experienced scientists to drive technological advancements.- Develop novel solutions to complex business problems in collaboration with partner teams.- Constructively critique peer research and mentor junior scientists and engineers- Contribute to Amazon's global science community through collaboration and publication of groundbreaking research.About the teamSupply Chain Optimization Technologies (SCOT) owns Amazon’s global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We decide how to place and move inventory within Amazon’s fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of world-wide. Venturing beyond traditional operations research methods for sequential decision-making in inventory planning. The team combines empirical research and real world testing, backed by a robust theoretical foundation. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

The Fulfillment by Amazon (FBA) team is looking for a passionate, curious, and creative Senior Applied Scientist, with expertise in machine learning (ML) and a proven record of solving business problems through scalable ML solutions, to join our top-notch cross-domain FBA science team. We want to learn seller behavior, understand seller experience, build automated LLM-based solutions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. We also predict potentially costly defects that may occur during packing, shipping, receiving and storing the inventory. We aim to prevent such defects before occurring while we are also fulfilling customer demand as quickly and efficiently as possible, in addition to managing returns and reimbursements. To do so, we build and innovate science solutions at the intersection of ML, statistics, economics, operations research, and data analytics. As a senior applied scientist, you will propose and deploy solutions that draw from a range of scientific areas such as supervised and unsupervised learning, recommendation systems, statistical learning, LLMs, and reinforcement learning. This role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate scientific work into production systems.Key job responsibilitiesAs a senior member of the science team, you will- play an integral role in building Amazon's FBA supply chain management system.- Research and develop ML models to solve diverse business problems faced in seller inventory management systems.- Define a long-term science vision and roadmap for the team, driven fundamentally from our customers' needs, translating those directions into specific plans for research.- Drive and execute ML projects/products end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring.- Review and audit modeling processes and results for other scientists, both junior and senior.- Advocate the right ML solutions to business stakeholders, engineering teams, as well as executive level decision makers.A day in the lifeIn this role, you will be a technical leader in ML with significant scope, impact, and visibility. As a senior scientist on the team, you will be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. From day one, you will be working with experienced scientists, engineers, and designers who love what they do. You are expected to make decisions about technology, models, and methodology choices. You will strive for simplicity, and demonstrate judgment backed by mathematical proof. You will also collaborate with the broader decision and research science community in Amazon to broaden the horizon of your work and mentor engineers and scientists. The successful candidate will have strong expertise in applying ML models in an applied environment and is looking for her/his next opportunity to innovate, build, deliver, and impress. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. The candidate will need to be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.About the teamFulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, allowing sellers to leverage Amazon’s world-class facilities to provide customers Prime delivery promise. Sellers gain access to Prime members worldwide, see their sales lift, and are free to focus their time and resources on what they do best while Amazon manages fulfillment. Over the last several years, sellers have enjoyed strong business growth with FBA shipping more than half of all products offered by Amazon. FBA focuses on helping sellers with automating and optimizing the third-party supply chain. FBA sellers leverage Amazon’s expertise in ML, optimization, data analytics, econometrics, and market design to deliver the best inventory management experience to sellers. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.BASIC QUALIFICATIONS- Master's degree in math/statistics/engineering or other equivalent quantitative discipline- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- Proficiency in model development, model validation, and model implementation with big data ...

Lead the development of cutting-edge AI models to power Amazon's eCommerce ontology - the authoritative source of product knowledge driving exceptional customer experiences. Applied Scientists in this role solve problems related to product classification, attribute extraction, ontology modeling, data integration and enrichment, and scalable knowledge services. It's challenging due to the vast scale, heterogeneous data sources, and evolving domains, but exciting for pushing boundaries in ML, NLP, and knowledge representation research.If you're passionate about driving innovation at scale, we want to hear from you!Key job responsibilities- Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology (Product Knowledge) at scale- Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources (seller listings, customer reviews, etc.)- Collaborate with engineers to design and implement robust services- Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge- Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing- Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community- Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Product KnowledgeA day in the lifeThe Amazon product ontology is a structured knowledge base representing product types, attributes, classes, and relationships. It standardizes product data, enabling enhanced customer experiences through improved search and recommendations, streamlined selling processes, and internal data enrichment across Amazon's eCommerce ecosystem.You will work with following stakeholders:- Product Managers represent customer experiences and selling partner experiences- Category Leaders (e.g., apparel, electronics) provide domain knowledge and guidance as subject matter experts- Engineers build and maintain data pipelines and services in production- Ontologists design data models and define guidelines - Other Applied Scientists collaborate on research and innovationAbout the teamThe Product Knowledge team at Amazon is dedicated to creating the industry-standard eCommerce product and services ontology. Our diverse team of applied scientists, engineers, ontologists and subject matter experts build a comprehensive ontology enabling exceptional customer and selling partner experiences through high-quality, contextual product knowledge at scale.BASIC QUALIFICATIONS- 4+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Join us in a historic endeavour to make Computer Vision accessible to the world with breakthrough research! The AWS AI Labs: Vision team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists develops the algorithms and models that have powered AWS computer vision services such as Amazon Rekognition, Amazon Textract, and Amazon Lookout for Vision. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. AWS is the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. Our research themes include, but are not limited to: few-shot learning, transfer learning, unsupervised and semi-supervised methods active learning and semi-automated data annotation, large scale image and video recognition, face detection and recognition, document OCR and scene text recognition, document understanding, 3D scene and layout understanding, and localization and mapping. We are hiring for all our locations in the USA (Seattle, Pasadena, Bay Area) and Israel (Haifa and Tel Aviv). About Us Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. About the teamAbout AWSDiverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS?Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Mentorship & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 3+ years of building models for business application experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Futures Design is the advanced concept design and incubation team within Amazon’s Device and Services Design Group (DDG). We are responsible for exploring and defining think (very) big opportunities globally and locally — so that we can better understand how new products and services might enrich the lives of our customers and so that product teams and leaders can align on where we're going and why we're going there. We focus on a 3–10+ year time frame, with the runway to invent and design category-defining products and transformational customer experiences. Working with Amazon business and technology partners, we use research, design, and prototyping to guide early product development, bring greater clarity to engineering goals, and develop a UX-grounded point of view.Our team is dedicated to unlocking new foundational capabilities in generative AI, guided by the thesis that embedding understanding through human factors, cognitive science, and socioeconomics is crucial to building AI systems that align with human needs. We place particular emphasis on the capabilities of simulacra through agentic systems and experiential/evolutionary learning, which we believe are vital to accelerating the development of AI as an aligned partner. Joining our team will give you the chance to drive key decisions that will impact the lives of millions of Amazon customers. Key job responsibilitiesYou will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).A day in the lifeWe're looking for a Senior Applied Scientist to join the growing DDG Futures Design team.You thrive in ambiguity and paradigm shifts – remaking assumptions of how customers engage, devices operate, and builders create. You apply deep expertise that spans design, technology, and product, grounding state-of-the-art emerging technologies through storytelling and a maker's mindset. You learn and adapt technology trends to enduring customer problems through customer empathy, code, and iterative experimentation.You will wear multiple hats to quickly assimilate customer problems, convert them to hypotheses, and test them using efficient technologies and design methods to build stakeholder buy-in. You’ll help your peers unlock challenging scenarios and mature the design studio’s ability to deliver design at scale across a breadth of devices and interaction modalities. You will work around limitations and push capabilities through your work. Your curiosity will inspire those around you and facilitate team growth, while your hands-on, collaborative nature will build trust with your peers and studio partners.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...