Senior Applied Scientist , Amazon Ads
Summary
Senior Applied Scientist at Amazon Ads builds and deploys large-scale machine learning models, including generative AI and LLMs, to power advertising systems serving billions of users daily.
Your Next Big Challenge Starts Here
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.
Watch Scientists at Amazon Ads Talk About Their Work
https://www.youtube.com/watch?v=vvHsURsIPEA
Learn More About Amazon Ads
https://advertising.amazon.com/
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.)
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.
Watch Scientists at Amazon Ads Talk About Their Work
https://www.youtube.com/watch?v=vvHsURsIPEA
Learn More About Amazon Ads
https://advertising.amazon.com/
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.)