2026 Fall Applied Science Internship Reinforcement Learning & Optimization (Machine Learning) United States, PhD Student Science Recruiting

Unlock the Future with Amazon Science!

Calling all visionary minds passionate about the transformative power of machine learning! Amazon is seeking boundary-pushing graduate student scientists who can turn revolutionary theory into awe-inspiring reality. Join our team of visionary scientists and embark on a journey to revolutionize the field by harnessing the power of cutting-edge techniques in bayesian optimization time series multi-armed bandits and more.

At Amazon we dont just talk about innovation we live and breathe it. Youll conducting research into the theory and application of deep reinforcement learning. You will work on some of the most difficult problems in the industry with some of the best product managers scientists and software engineers in the industry. You will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised semi-supervised and unsupervised learning reinforcement learning advanced statistical modeling and graph models.

Throughout your journey youll have access to unparalleled resources including state-of-the-art computing infrastructure cutting-edge research papers and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically communicate effectively and thrive in a fast-paced innovative environment where bold ideas are celebrated.

Join us at the forefront of applied science where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn grow and leave an indelible mark on the world of technology.

Amazon has positions available for Machine Learning Applied Science Internships in but not limited to Arlington VA; Bellevue WA; Boston MA; New York NY; Palo Alto CA; San Diego CA; Santa Clara CA; Seattle WA.

Key job responsibilities
We are particularly interested in candidates with expertise in: Optimization Programming/Scripting Languages Statistics Reinforcement Learning Causal Inference Large Language Models Time Series Graph Modeling Supervised/Unsupervised Learning Deep Learning Predictive Modeling

In this role you will work alongside global experts to develop and implement novel scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Reinforcement Learning and Optimization within Machine Learning. You will tackle challenging groundbreaking research problems on production-scale data with a focus on developing novel RL algorithms and applying them to complex real-world challenges.

The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter comfortable with ambiguity with strong attention to detail and the ability to thrive in a fast-paced ever-changing environment.

A day in the life
- Develop scalable efficient automated processes for large scale data analyses model development model validation and model implementation.
- Design development and evaluation of highly innovative ML models for solving complex business problems.
- Research and apply the latest ML techniques and best practices from both academia and industry.
- Think about customers and how to improve the customer delivery experience.
- Use and analytical techniques to create scalable solutions for business problems.

- Are enrolled in a PhD
- Can relocate to where the internship is based
- Experience programming in Java C Python or related language
- Experience with one or more of the following: Optimization Programming/Scripting Languages Statistics Reinforcement Learning Causal Inference Large Language Models Time Series Graph Modeling Supervised/Unsupervised Learning Deep Learning Predictive Modeling
- Experience with one or more of the following: Optimization Programming/Scripting Languages Statistics Reinforcement Learning Causal Inference Large Language Models Time Series Graph Modeling Supervised/Unsupervised Learning Deep Learning Predictive Modeling
- Must be available for full-time (40 hours per week) internship for the whole duration of the internship

- Have publications at top-tier peer-reviewed conferences or journals
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The starting pay for this position is listed below. Final starting pay will be based on factors including experience qualifications and location. Starting Day 1 of employment Amazon offers EAP Mental Health Support Medical Advice Line 401(k) matching. Learn more about our benefits at OR Corvallis - 142800.00 - 193200.00 USD annually
USA WA SEATTLE - 142800.00 - 193200.00 USD annually
USA WA Seattle - 142800.00 - 193200.00 USD annually