Applied Scientist, Amazon Supply Chain

About the role

As part of the AWS Applied AI Solutions organization, we are building revolutionary enterprise applications that leverage machine learning, generative AI, and agentic AI to help millions of companies worldwide manage their day-to-day supply chain operations. Our mission is to accelerate customers' businesses through intuitive, differentiated technology solutions that solve enduring supply chain challenges. We blend strategic vision with curiosity and Amazon's real-world operational experience to build opinionated, turnkey solutions that make the 'buy versus build' decision a no-brainer for our customers.

As an Applied Scientist, you will design and develop state-of-the-art machine learning models and algorithms that power intelligent supply chain applications at global scale. You will work at the intersection of research and real-world product impact—translating scientific breakthroughs into production systems that serve millions of customers. We operate like a startup within AWS, offering the opportunity to tackle unprecedented challenges while working with the latest technologies in deep learning, large language models, and optimization.

Responsibilities

• Design, develop, and deploy machine learning models for demand forecasting, inventory optimization, anomaly detection, and supply chain decision-making, with guidance from senior scientists on novel problem spaces.
• Contribute to GenAI and Agentic AI solutions that automate supply chain workflows; implement model components, pipelines, and evaluation harnesses.
• Formulate well-scoped business problems as ML problems; define data requirements, model architectures, evaluation metrics, and experimentation plans.
• Drive applied science projects end-to-end — from prototyping through offline evaluation, A/B testing, and production deployment — with increasing autonomy.
• Publish research in top-tier conferences (NeurIPS, ICML, KDD, AAAI) and contribute to patent filings.
• Raise the technical bar through code reviews, design feedback, and knowledge-sharing sessions.
• Collaborate with engineering, product, and business stakeholders to translate scientific capabilities into customer-facing features; communicate results to technical and non-technical audiences.
• Stay current with state-of-the-art AI/ML research; identify and propose opportunities to apply emerging techniques to existing problems.
• Follow and contribute to best practices for experimentation, model validation, and responsible AI development.

About the team

The AWS Applied AI Solutions team builds enterprise applications that leverage Amazon's operational expertise to solve real-world supply chain challenges for millions of companies. We operate like a startup within AWS—moving fast, shipping iteratively using state-of-the-art AI technologies. We invest in your growth through mentorship from senior scientists, conference publication support, and internal science reading groups.

Amazon values diverse experiences—even if you don't meet all preferred qualifications, we encourage you to apply. If your career hasn't followed a traditional path, don't let that stop you.

Qualifications

Basic Qualifications

• PhD in computer science, computer engineering, or related field.
• Experience applying theoretical models in an applied environment.
• Experience implementing algorithms using both toolkits and self-developed code.
• Experience building machine learning models or developing algorithms for business application.
• Experience with or exposure to generative AI, large language models (LLMs), or agentic AI systems (e.g., multi-step reasoning, tool-use, autonomous workflow orchestration).

Preferred Qualifications

• Experience with demand forecasting, time-series modeling, or supply chain optimization.
• Hands-on experience building agentic AI pipelines — including prompt engineering, retrieval-augmented generation (RAG), and multi-agent orchestration.
• Experience designing and analyzing A/B tests at scale.
• Demonstrated ability to translate ambiguous business problems into well-defined ML solutions.
• Publications in top-tier conferences (NeurIPS, ICML, KDD, AAAI) or equivalent venues.
• Experience working with large-scale distributed systems (e.g., Spark, AWS services).
• Strong written and verbal communication skills; ability to present technical work to non-technical stakeholders.

Benefits

Amazon offers comprehensive benefits including:

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans).
• Employee Assistance Program (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 amazon.jobs/en/benefits.

Pay

The base salary range for this position in Seattle, WA is $142,800 - $193,200 USD annually. 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.