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# Sr. Applied Scientist, Amazon Ads

- **Company:** Amazon.com, Inc.
- **Location:** Corvallis, OR, United States
- **Experience:** Expert
- **Salary:** $167,100.0 - $226,100.0
- **Contract:** Permanent contract
- **Skills:** Mxnet, Java (Programming Language), Computer Vision, Big Data, Business Software, C++ (Programming Language), Distributed Systems, R (Programming Language), Apache Hadoop, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Recommender Systems, Software Tools, Tensorflow, SciPy, Large Language Models, Apache Spark, Deep Learning, Spark Mllib, Scikit Learn, Data Generation
- **Published:** June 11, 2026
- **Apply:** https://www.juju.com/job/00000000g73e9h

## About the Role

5+ 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.

## Description

As a Senior Applied Scientist in Amazon Ads, you will:

 - Research and implement cutting-edge ML approaches, including applications of generative AI and large language models

 - Develop and deploy innovative ML solutions spanning multiple disciplines - from ranking and personalization to natural language processing, computer vision, recommender systems, and large language models

 - Drive end-to-end projects that tackle ambiguous problems at massive scale, often working with petabytes of data

 - Build and optimize models that balance multiple stakeholder needs - helping customers discover relevant products while enabling advertisers to achieve their goals efficiently

 - Build ML models, perform proof-of-concept, experiment, optimize, and deploy your models into production, working closely with cross-functional teams including engineers, product managers, and other scientists

 - Design and run A/B experiments to validate hypotheses, gather insights from large-scale data analysis, and measure business impact

 - Develop scalable, efficient processes for model development, validation, and deployment that optimize traffic monetization while maintaining customer experience


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