Senior Applied Scientist , Amazon Ads

About the role

Join Amazon Ads to apply your machine learning expertise at a scale that impacts billions of people daily. You'll work on generative AI, large language models, and next-generation ML to reinvent advertising—from campaign creation to customer discovery. Your work will power billions of impressions, millions of clicks, and petabytes of data, driving real-world impact.

Why this role excites

• Unmatched scale and resources: Access computational power and datasets that enable planet-scale solutions.
• Breadth of challenges: Work across real-time bidding, creative AI, ranking, personalization, NLP, computer vision, and LLMs.
• Direct impact: Take models from concept to production, run A/B experiments, and see your work move business metrics.
• Collaborative environment: Work 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, to transform advertising.
• Own end-to-end projects: from ambiguous problems to deployed, production-grade models.
• Design experiments to validate hypotheses and measure real business impact.
• Build models that balance customer and advertiser needs, ensuring advertising feels helpful, not intrusive.
• Collaborate cross-functionally with engineers, PMs, and scientists to ship fast and iterate.
• Develop scalable ML pipelines that optimize monetization without sacrificing customer experience.

Career growth

• Lead high-visibility technical initiatives and mentor other scientists.
• Shape strategy alongside senior leadership.
• Build a reputation in a community that values scientific excellence.
• Opportunities for both deep technical growth and people leadership.
• 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

Compensation includes base salary, sign-on payments, and restricted stock units (RSUs). Final compensation determined by experience, qualifications, and location.

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, and optional supplemental life plans).
• Employee Assistance Program (EAP) and mental health support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and surrogacy reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.

Learn more about benefits at amazon.jobs/en/benefits.