Senior Applied Scientist , Amazon Ads

Amazon.com, Inc.
New York, NY, United States
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$192,200.0 - $260,000.0
Working hours
Regular working hours
Job source

Tech stack

Mxnet Java (Programming Language) Artificial Intelligence Artificial Neural Networks Computer Vision Business Software C++ (Programming Language) Computer Programming Distributed Systems R (Programming Language) Apache Hadoop Python (Programming Language)
+14 more
Machine Learning Natural Language Processing NumPy Software Tools Tensorflow SciPy Pytorch Large Language Models Apache Spark Deep Learning Generative AI Spark Mllib Scikit Learn Machine Learning Operations

Job description

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.

Requirements

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.), * 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.

Benefits & conditions

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 .

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