This role sits at the intersection of Agentic AI, LLMs, reinforcement learning, multimodal reasoning, and large-scale distributed systems. As an Applied Scientist, you will help define the science and architecture powering internet-scale web agents and autonomous purchasing systems.
In this role, you will:
- Work on autonomous AI agents operating in open-world environments rather than static benchmarks.
- Solve challenging research problems at the intersection of LLMs, web interaction, multimodal reasoning, and scalable systems.
- Influence products that directly impact millions of Amazon customers.
- Build systems that must generalize across thousands of constantly evolving third-party websites.
- Partner closely with science, engineering, and product leaders to shape the future of AI-powered shopping experiences.
- Have the opportunity to publish research, file patents, and contribute to Amazon-wide AI innovation.
Key job responsibilities
- Design scalable evaluation and benchmarking systems for autonomous agents operating in dynamic web environments.
- Develop techniques for robust agent planning, error recovery, and adaptation under distribution shift.
- Build multimodal AI systems that reason over screenshots, DOM structures, user intent, and interaction trajectories.
- Lead scientific direction for agent reliability, task completion, and customer trust.
- Mentor scientists and engineers on advanced AI methodologies and experimentation.
About the team
The Buy For Me purchasing team owns the mission of completing customer purchases on off-amazon sites through both deterministic protocols and agentic methods. This role is with the agentic purchase team which is comprised of both SDEs and Applied Scientists working closely on production agents and offline capabilities to explore off-amazon sites, validate purchasing quality and onboard new sites to the Buy For Me program.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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
