A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Agentic AI solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to improve customer experience, moving fast to ship solutions and then iterating on user feedback and interactions.
Key job responsibilities
- Leverage your technical expertise to lead the development of Large Language Model (LLM) technologies.
- Tackle complex problems in LLM modeling and engineering.
- Set direction and collaborate with applied scientists and engineers.
- Research and develop techniques to reduce friction and enable scientific solutions for products Analyze and improve customer experiences using Amazon's diverse data sources and computing resources.
- Work on core LLM technologies, including: Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF) and Evaluation methodologies.
- Your work will directly impact customers through novel products and services.
A day in the life
- Partner with stakeholders to identify science strategies and solutions for business problems
- Analyze, understand, and model customer experience risk with Amazon products and services with passion towards solving for international customer-centric challenges.
- Develop and build novel online and offline evaluation metrics, focus on international customer specific model performance tuning.
- Quickly experiment and setup experimentation framework for agile model and data analysis
- Deploy science models to production systems in partnership with the engineering team
- Lead junior scientists to contribute to industry first research and to drive the innovation forward.
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!
Benefits summary:
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:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
About the team
Customer Experience Risk Services (CXRS) is focused on making Amazon the most trusted company on earth for consumers, advertisers, developers, creators, selling partners (and more to come). We build risk products and machine learning services to scale expert knowledge and learnings from past projects for business teams to identify risks prior to launching external products and services.
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
- PhD in math/statistics/engineering or other equivalent quantitative discipline, or Master's degree
- Solid ML background and familiar with standard NLU, NLG, and LLM techniques
PREFERRED QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience with conducting research in a corporate setting
- Experience in applied research
- Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, etc.)
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.