2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning)[...]

Amazon

Corvallis (OR)

On-site

USD 143,000 - 193,000

Full time

3 days ago
Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

EAP
Mental Health Support
Medical Advice Line
401(k) matching

Job summary

Amazon Science is seeking graduate student scientists to turn cutting-edge theory into impactful practice. You will conduct research in deep reinforcement learning, Bayesian optimization, time series, and ML modeling, collaborating with product managers, scientists, and engineers to deploy scalable algorithms on production data.

The role emphasizes exploration of supervised, semi-supervised, and unsupervised learning, with access to state-of-the-art infrastructure and mentorship, in a

Qualifications

  • Enrolled in a PhD program.
  • Willing to relocate to the internship location.
  • Proficient in Java, C++, Python or related language.
  • Experience in Optimization, RL, Time Series, Graph Modeling, DL, and Predictive Modeling.

Responsibilities

  • Develop scalable ML models and algorithms for production-scale data analysis and modeling.
  • Research and implement RL/Optimization techniques to advance state-of-the-art in ML.
  • Collaborate with cross-functional teams of product managers, scientists, and software engineers.

Skills

Java
C++
Python
Optimization
Reinforcement Learning
Time Series
Graph Modeling
Deep Learning
Predictive Modeling
Large Language Models

Education

PhD

Job description

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, 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.
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
  • 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

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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t 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.

  • EAP
  • Mental Health Support
  • Medical Advice Line
  • 401(k) matching

Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits .

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

Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning)[...]
2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning)[...]

Amazon • Seattle (WA)

On-site
USD 41,328 - 55,104
Access to state-of-the-art resources
Mentorship from industry leaders
Immersive experience in AI research
2026 Fall Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Lear[...]
2026 Fall Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Lear[...]

Amazon • Seattle (WA)

On-site
USD 142,800 - 193,200
EAP and Mental Health Support
401(k) matching
Cutting-edge resources and mentorship
2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - [...]
2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - [...]

Amazon • Seattle (WA)

On-site
USD 142,800 - 193,200
401(k) matching
Mental Health Support
Medical Advice Line
2026 Fall Research Science Internship - United States, PhD Student Science Recruiting
2026 Fall Research Science Internship - United States, PhD Student Science Recruiting

Amazon • Corvallis (OR)

On-site
USD 136,000 - 184,000
2026 Fall Research Science Internship - United States, PhD Student Science Recruiting
2026 Fall Research Science Internship - United States, PhD Student Science Recruiting

Amazon • United States

Hybrid
USD 136,000 - 184,000
EAP
Mental Health Support
401(k) matching
2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & [...]
2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & [...]

Amazon • San Francisco (CA)

On-site
USD 171,600 - 222,200
401(k) matching
Mental Health Support
Medical Advice Line
2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & [...]
2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & [...]

Amazon • Seattle (WA)

On-site
USD 142,000 - 194,000
2026 Fall Applied Science Internship Information Knowledge Management
2026 Fall Applied Science Internship Information Knowledge Management

Amazon • Boston (MA)

On-site
USD 142,000 - 194,000
Applied Science Robotics Intern — AI, Vision & Control
Applied Science Robotics Intern — AI, Vision & Control

Amazon • San Francisco (CA)

On-site
USD 171,600 - 222,200
401(k) matching
Mental Health Support
Medical Advice Line
2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier[...]
2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier[...]

Amazon • San Francisco (CA)

On-site
USD 157,000 - 213,000
EAP
Mental Health Support
401(k) matching