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Reinforcement Learning Intern Jobs (NOW HIRING)

Workato

Intern, AI Engineering

San Francisco, CA

We are now filling intern positions for Winter 2026 and Spring 2027. Research Areas * LLM Agent ... Develop novel methods for parameter-efficient adaptation, alignment, and reinforcement learning for ...

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How much do reinforcement learning intern jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for reinforcement learning intern in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What kinds of projects or tasks can I expect to work on as a Reinforcement Learning Intern?

As a Reinforcement Learning Intern, you will typically work on tasks such as designing, implementing, and testing reinforcement learning algorithms, analyzing experimental results, and assisting with data preprocessing or environment development. You may also collaborate with senior researchers and engineers, participate in code reviews, and contribute to technical discussions or team meetings. In many organizations, interns are given the chance to work on real-world problems—ranging from optimizing robotic control systems to enhancing recommendation engines. This hands-on experience not only builds your technical expertise but also helps you develop valuable teamwork and communication skills, preparing you for a future career in AI or machine learning.

What is a Reinforcement Learning Intern job?

A Reinforcement Learning (RL) Intern is responsible for researching, developing, and testing RL algorithms to solve complex problems. They typically work on tasks such as implementing reinforcement learning models, optimizing reward functions, and running experiments in simulated environments. Interns collaborate with researchers and engineers to refine models and improve the efficiency of RL systems. They usually have experience in machine learning, deep learning, and programming languages like Python. The role provides hands-on experience in applying RL techniques to real-world applications.

What are the key skills and qualifications needed to thrive in the Reinforcement Learning Intern position, and why are they important?

To thrive as a Reinforcement Learning Intern, you need strong knowledge of machine learning fundamentals, programming proficiency (usually in Python), and a background in mathematics or computer science, often demonstrated through academic coursework or relevant projects. Familiarity with popular machine learning libraries such as TensorFlow, PyTorch, and RL-specific frameworks like OpenAI Gym is typically expected. Effective problem-solving skills, attention to detail, and the ability to communicate technical findings clearly are valuable soft skills in this position. These capabilities enable interns to contribute meaningfully to research and development efforts, bridging theory and practical application in real-world reinforcement learning projects.

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Reinforcement Learning Intern jobs near you
Intern - Reinforcement Learning Engineer

Intern - Reinforcement Learning Engineer

Ghost Robotics

Philadelphia, PA

$30 - $45/hr

Other

Posted 17 days ago

Job description

Reinforcement Learning Intern

Ghost Robotics is the industry leader in legged robotic systems that not only help our customers solve complex operational, national security, and technical challenges to save lives, reduce harm and improve outcomes.

We are looking for a part-time Reinforcement Learning Intern to work with the Chief Science Officer to develop reinforcement learning algorithms for quadrupedal robot self-righting.

Key Duties:

  • Develop infrastructure - scripts for training and evaluating algorithm progress
  • Use mjlab for training in simulation, with domain randomization for zero-shot sim2sim and sim2real transfer
  • Hands-on testing on the physical robot
  • Reward tuning for desirable performance

Requirements:

  • Holds Bachelor's degree in Computer Engineering, Software Engineering, or a related field
  • Currently pursuing Masters degree in Computer Engineering, Software Engineering, or a related field
  • Expertise in reinforcement learning algorithms like PPO, TRPO
  • Experience with weights & biases dashboard setup
  • Python programming experience
  • Mjlab or Isaac sim experience
  • Optional but highly desirable: taken ESE 6510 Physical Intelligence course at Penn (or equivalent)

Location:

Philadelphia, PA (no remote candidates considered at this time).

Schedule and Commitment:

Flexible, part-time schedule, 20 - 30 hours per week. Able to commit to three (3) month minimum project, with option to extend following evaluation.

Travel:

No Travel Required.

Compensation:

Competitive base $30 - $45 per hour.

Background Check:

Clear standard background checks, pre-hire, post hire and anytime during employment as required.

Residency Requirements:

Employment Authorization Required.

Intellectual Property:

Note: An IP agreement needs to be signed for this project, and any public release of project outputs requires prior company approval.

Physical Requirements:

  • Prolonged periods of standing, sitting at a desk and working on a computer.
  • Must be able to lift 20 pounds. Assistive equipment available.

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