Sr Applied Scientist, Amazon Supply Chain

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.

We are looking for a Senior 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 a Senior 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 novel machine learning models for demand forecasting inventory optimization anomaly detection and supply chain decision-making.
• Lead the development of GenAI and Agentic AI solutions that automate complex supply chain workflows and deliver intelligent adaptive recommendations to customers.
• Formulate real-world business problems as machine learning problems; define data requirements model architectures evaluation metrics and experimentation frameworks.
• Drive end-to-end applied science projects from ideation through experimentation offline evaluation A/B testing and production deployment at scale.
• Publish research findings in top-tier conferences (NeurIPS ICML KDD AAAI) and file patents to advance Amazon's intellectual property.
• Mentor and develop junior scientists; raise the technical bar for the science team through code reviews design reviews and knowledge sharing.
• Collaborate closely with engineering product management and business stakeholders to translate scientific capabilities into customer-facing product features.
• Influence the technical strategy and scientific roadmap for the organization; identify new areas of investment and emerging opportunities in AI/ML.
• Establish and promote best practices for experimentation model validation and responsible AI development across the team. About the team 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.

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.

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.

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.

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 or equivalent research experience

- 6+ years of building machine learning models for business application experience

- Knowledge of programming languages such as C/C++, Python, Java or Perl

- Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in software development

- Have peer-reviewed scientific contributions in premier journals and conferences

Preferred qualifications

- Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

- Knowledge of supply chain management concepts - forecasting, planning, sourcing, optimization and logistics or equivalent

- 5+ years of building large-scale machine learning and AI solutions at Internet scale experience

- Experience in supply chain

- Experience in practical work applying ML to solve complex problems for large scale applications

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 - 167,100.00 - 226,100.00 USD annually