2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting
Description
Unlock the Future with Amazon Science!
We are seeking boundary-pushing graduate student scientists passionate about the transformative power of machine learning. 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 don't just talk about innovation – we live and breathe it. You'll conduct 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, you'll 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.
Amazon Locations
- Arlington, VA
- Bellevue, WA
- Boston, MA
- New York, NY
- Palo Alto, CA
- San Diego, CA
- Santa Clara, CA
- Seattle, WA
Key Job Responsibilities
- 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.
- 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.
- Work collaboratively with diverse groups and cross-functional teams to solve complex business problems.
- Think about customers and how to improve the customer delivery experience.
- Use and analytical techniques to create scalable solutions for business problems.
Basic Qualifications
- 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
- Must be available for full-time (40 hours per week) internship for the whole duration of the internship
Preferred Qualifications
- 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
Pay
- USA, OR, Corvallis - 142,800.00 - 193,200.00 USD annually
- USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually
- USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually