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We are looking for an Applied Scientist to join our team that is building revolutionary enterprise applications leveraging 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 our 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 you the opportunity to tackle unprecedented challenges while working with the latest technologies in deep learning, large language models, and optimization.
If you are passionate about pushing the boundaries of applied science, thrive in ambiguous problem spaces, and want to shape the future of supply chain intelligence while having the backing of AWS's extensive resources, we want to hear from you.
Key job 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.
ABOUT AWS:
Diverse Experiences
Amazon 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.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We’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. 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.
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
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