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.)
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
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