The OTS DataTech team drives enterprise data strategy and support across OTS. Our charter encompasses OTS-wide efforts, including Data as a Product (DaaP), enterprise data infrastructure, AI/ML capability, and supporting specific business-critical programs, fueling innovation and automation for OTS.
We are looking for a passionate, talented, innovative, experienced and Senior Machine Learning Scientist with a background in building cutting-edge scientific and engineering components that are highly scalable, extensible, and robust to enable exponential growth and adoption of AI/ML within OTS. In this role, you will play a pivotal role in shaping the vision, roadmap, and execution of science and engineering-based solutions from beginning to end.
You will build foundational GenAI components that will enable our customers to build GenAI applications for their use cases across OTS. You will enable the seamless integration of scientific products with new and existing systems, ultimately leading to increased operational efficiency and productivity across OTS. You will also work on projects involving supervised and unsupervised learning, NLP, and more. You will be responsible to build and maintain an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases within the realms of GenAI, supervised and unsupervised learning, optimization, and more.
You will evangelize the adoption of our scientific solutions across the organization. You will be closely partnering with a cross-functional team of stakeholders including with Applied Scientists, Data Scientists, Data Engineers, Product Managers, and Technical Program Managers.
As part of other initiatives, you will also contribute to building a data infrastructure that supports our DataMesh framework, enabling engineering and BI self-service architecture for DaaP, 3P software integrations, and more.
Come join OTS DataTech as we continue to innovate and pioneer the AI/ML space within OTS!
Key job responsibilities
* Build and maintain an MLOps Platform that supports end-to-end AI/ML operations.
* Shape the vision and roadmap for AI/ML across the organization, leading their research and development from concept to deployment from an engineering perspective.
* Guide teams to adopt software engineering best practices that uplift our Operational Excellence standards.
* Promote and facilitate the adoption of AI/ML solutions across the organization.
* Build and maintain data infrastructure that supports the DataMesh framework and enables self-service architecture.
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
BASIC QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of industry or academic research experience
- 5+ years of applied research experience
- 5+ years of building machine learning models or developing algorithms for business application experience
- 5+ years of industry or academic research experience
- Experience programming in Java, C++, Python or related language
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
PREFERRED QUALIFICATIONS
- 5+ years of experience in full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience developing, building and implementing complex software systems and machine learning systems that have been successfully delivered to customers.
- Experience developing, building, and implementing data engineering pipelines and infrastructure.
- Experience with AWS technologies.
- Experience with MLOps tools and frameworks (e.g., SageMaker, MLflow).
- Background in AI/ML, including GenAI, supervised and unsupervised learning, and optimization algorithms.
- Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain).
- Publications at top-tier peer-reviewed conferences or journals.
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.