Amazon.com Services LLC
Applied Science, studentprograms
2026FallAppliedScienceInternship-ReinforcementLearning&Optimization(MachineLearning)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) at Amazon.com Services LLC. Skills: Reinforcement Learning, Optimization, Machine Learning, Deep Learning. Conduct research into theory and application of deep. Propose and deploy solutions”
Industry & Context.
Solve complex business problems
Relocate to internship location
What They're Looking For.
Must Have
Enrolled in a PhD, Experience programming in Java, C++, Python, Experience with Optimization, Experience with Programming/Scripting Languages, Experience with Statistics, Experience with Reinforcement Learning, Experience with Causal Inference, Experience with Large Language Models, Experience with Time Series, Experience with Graph Modeling, Experience with Supervised/Unsupervised Learning, Experience with Deep Learning, Experience with Predictive Modeling, Available for full-time internship
Nice to Have
Publications at top-tier conferences, Publications at top-tier journals, Experience in state-of-the-art deep learning models architecture design, Experience in deep learning training and optimization, Experience in model pruning
What You'll Do.
Conduct research into theory and application of deep
Propose and deploy solutions
Develop and implement novel algorithms
Develop and implement modeling techniques
Tackle research problems on production-scale data
Develop novel RL algorithms
Apply RL algorithms to real-world challenges
Develop scalable processes for data analyses
Develop scalable processes for model development
Develop scalable processes for model validation
Develop scalable processes for model implementation
Research ML techniques
Think about customers
Improve customer delivery experience
Use analytical techniques
Create scalable solutions
How You'll Work.
Team & Collaboration
Work with product managers; Work with scientists; Work with software engineers; Work with global experts; Work with diverse groups; Work with cross-functional teams
Communication Scope
Communicate effectively
Full Job Description
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 don't just talk about innovation – we live and breathe it. You'll 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, 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. 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
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