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, petabytes of data — and you at the center of it.
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: one quarter you might optimize real-time bidding systems, the next build creative AI that generates ad content. Ranking, personalization, NLP, computer vision, LLMs — it's all on the table.
- 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 — 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.
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 genuinely 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 insurance, and option for Supplemental life plans).
- Employee Assistance Program (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 amazon.jobs/en/benefits.