To this end, the Science team is tasked with:
• Building and deploying AI / ML models and LLM-powered systems that lead to hundreds of millions in business impact across supply chain optimization, customer engagement, and cultural relevance at Amazon scale
• Partnering with product teams in evaluating the financial and operational impact of new product offerings.
• Partnering with science teams across other organizations to develop state of the art algorithms and models.
• Carrying out independent data-backed initiatives that can be leveraged later on in the fields of network organization and financial modeling of processes.
• Publishing papers in both internal and external conferences / journals.
In order to execute the above mandate we are on the look out for smart and qualified Applied Scientists who will own projects in partnership with product and research teams as well as operate autonomously on independent initiatives that are expected to unlock benefits in the future. Our team builds science-backed systems that directly influence vendor negotiations, forecasting, buying, product discovery for secondary language customers, and inventory management for North America's retail business.
Key job responsibilities
As an Applied Scientist, you are able to use a range of artificial intelligence and operations research methodologies to solve challenging business problems when the solution is unclear. Key responsibilities include:
Develop workflows that combine ML models with optimization engines, similarity search, and human-in-the-loop capabilities to automate complex business processes
Build scalable data and inference pipelines using AWS services (SageMaker, Bedrock, FAISS, Andes) to process 100M+ ASINs and serve real-time predictions in production
Design and execute rigorous experimentation frameworks including weblabs, IPC labs, and causal inference methods to validate model impact and drive launch decisions
Collaborate cross-functionally with engineering, product, and business teams to translate ambiguous business problems into well-scoped science solutions with clear success metrics
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
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
- Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
- Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
