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 not just running 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. Petabytes of data. And you — at the center of it.

Why this role will excite you

• Unmatched scale and resources. You'll have access to computational power and datasets most scientists only dream about. Build solutions that don't just work in a notebook — they work at planet scale.
• Breadth that keeps you sharp. One quarter you might be optimizing real-time bidding systems. The next, you're building creative AI that generates ad content. Ranking, personalization, NLP, computer vision, LLMs — it's all on the table.
• Your ideas ship. This isn't a research lab where papers collect dust. You'll 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. You'll collaborate with world-class engineers, scientists, and product leaders who are just as passionate about solving hard problems as you are.

What you'll actually do

• 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 — because great advertising should feel 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

Where this takes your career

Whether you want to go deep as a technical IC 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 genuinely values scientific excellence

Your work won't just be seen internally — it'll impact millions of customers and advertisers worldwide.

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: $192,200.00 - $260,000.00 USD annually
• USA, CA, Santa Monica: $167,100.00 - $226,100.00 USD annually
• USA, CA, Sunnyvale: $192,200.00 - $260,000.00 USD annually
• USA, MA, Boston: $167,100.00 - $226,100.00 USD annually
• USA, MD, Washington DC: $167,100.00 - $226,100.00 USD annually
• USA, NY, New York: $183,800.00 - $248,700.00 USD annually
• USA, NY, New York City: $183,800.00 - $248,700.00 USD annually
• USA, VA, Arlington: $167,100.00 - $226,100.00 USD annually
• USA, WA, Bellevue: $167,100.00 - $226,100.00 USD annually
• USA, WA, SEATTLE: $167,100.00 - $226,100.00 USD annually

Benefits

• 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
• Parental leave

This response is AI-generated, for reference only.