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 will be at your fingertips.

Why this role excites 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.
• 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 messy, ambiguous problems to deployed, production-grade models.
• Design experiments that validate your hypotheses and measure real business impact.
• Build models that balance what's best for customers and advertisers — ensuring advertising feels helpful, not intrusive.
• Work cross-functionally with engineers, PMs, and fellow 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 individual contributor or grow into people leadership, both paths are real here. You'll have opportunities to:

• Lead high-visibility technical initiatives.
• Mentor and grow other scientists.
• Shape strategy alongside senior leadership.
• Build 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, 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

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with options for supplemental life plans).
• Employee Assistance Program (EAP) and 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 amazon.jobs/en/benefits.