Applied Scientist, SPX AI Lab

Job | Services LLC

Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide.

We are seeking a world‑class Applied Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top‑tier product managers and engineers to launch production‑grade agentic capabilities at Amazon's scale — owning your problem space end‑to‑end, from a crisp customer insight to a shipped product that millions of sellers rely on.

Key job responsibilities

• Use state-of-the-art Agentic AI and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.
• Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions.
• Work closely with teams of scientists and software engineers to drive real‑time model implementations and deliver novel and highly impactful features.
• Establish scalable, efficient, automated processes for large‑scale data analyses, model benchmarking, model validation and model implementation.
• Research and implement novel machine learning and statistical approaches.
• Participate in strategic initiatives to employ the most recent advances in AI in a fast‑paced, experimental environment.

About the team

Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production‑grade, multi‑agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer‑obsessed company, transforming the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

Basic

Qualifications

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• 3+ years of building machine learning models or developing algorithms for business application experience
• 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 in patents or publications at top‑tier peer‑reviewed conferences or journals
• Experience in investigating, designing, prototyping, and delivering new and innovative system solutions

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 (Use the "Apply for this Job" box below). 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 - 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. 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 .

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