Senior Applied Scientist , Amazon Ads

About the Role

You've spent years mastering machine learning. Now imagine applying that expertise where it actually reaches billions of people—every single day. At Amazon Ads, we're re-inventing the entire advertising experience using generative AI, large language models, and next-generation ML. From the moment a brand crafts a campaign to the instant a customer discovers something they love—your science powers it all. Billions of impressions, millions of clicks, and petabytes of data are at the center of what you'll work on.

Why This Role Will Excite You

• Unmatched scale and resources: Access to computational power and datasets most scientists only dream about. Build solutions that work at planet scale.
• Breadth that keeps you sharp: Work across real-time bidding systems, creative AI, ranking, personalization, NLP, computer vision, and LLMs—all in one role.
• Your ideas ship: Take models from concept to production, run A/B experiments, and see your work move metrics that matter for advertisers, customers, and the business.
• People who push you forward: Collaborate with world-class engineers, scientists, and product leaders passionate about solving hard problems.

Responsibilities

• Research and build next-generation ML solutions—including generative AI and LLM applications—that transform how advertising works.
• Own end-to-end projects: from ambiguous problems to deployed, production-grade models.
• Design experiments to validate hypotheses and measure real business impact.
• Build models that balance customer and advertiser needs—great advertising should feel helpful, not intrusive.
• Work cross-functionally with engineers, PMs, and scientists to ship fast and iterate faster.
• Develop scalable ML pipelines that optimize monetization without sacrificing customer experience.

Career Growth

Whether you want to go deep as a technical IC or grow into people leadership, both paths are real here. Opportunities include:

• Leading high-visibility technical initiatives.
• Mentoring and growing other scientists.
• Shaping strategy alongside senior leadership.
• Building a reputation in a community that values scientific excellence.

Your work will impact millions of customers and advertisers worldwide.

Qualifications

Basic Qualifications:

• 5+ years building ML models for real business applications.
• PhD, or Master's degree + 6 years of applied research experience.
• Strong programming skills in Python, Java, C++, or similar.
• Hands-on experience with deep learning and neural network methods.

Preferred Qualifications:

• Experience with tools like scikit-learn, TensorFlow, PyTorch, Spark MLLib, MxNet, numpy, or scipy.
• Experience with large-scale distributed systems (Hadoop, Spark, etc.).

Pay

• USA, CA, Palo Alto: $192,200 - $260,000 USD annually
• USA, CA, Santa Monica: $167,100 - $226,100 USD annually
• USA, CA, Sunnyvale: $192,200 - $260,000 USD annually
• USA, MA, Boston: $167,100 - $226,100 USD annually
• USA, MD, Washington DC: $167,100 - $226,100 USD annually
• USA, NY, New York: $183,800 - $248,700 USD annually
• USA, NY, New York City: $183,800 - $248,700 USD annually
• USA, VA, Arlington: $167,100 - $226,100 USD annually
• USA, WA, Bellevue: $167,100 - $226,100 USD annually
• USA, WA, Seattle: $167,100 - $226,100 USD annually

Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location.

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D, and optional supplemental life plans).
• Employee Assistance Program (EAP), Mental Health Support, and 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.