ZipRecruiter

Log In

1

Reinforcement Learning Internship Jobs (NOW HIRING)

Faire

Data Science Intern

San Francisco, CA

$75/hr

Data Science Internship - Fall 2026 Faire leverages machine learning and data insights to transform ... Apply exploration-exploitation strategies - including contextual bandits and reinforcement learning ...

next page

Showing results 1-20

All JobsReinforcement Learning JobsReinforcement Learning Internship Jobs

Reinforcement Learning Internship information

See salary details

$8

$17

$24

How much do reinforcement learning internship jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for reinforcement learning internship 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 are some common challenges faced during a Reinforcement Learning Internship and how can I prepare for them?

As a Reinforcement Learning Intern, you may encounter challenges such as tuning hyperparameters, managing computational resources, and understanding the intricacies of reward design. Interns often work with large datasets and complex environments, which can be resource-intensive and require efficient coding skills. To prepare, it's helpful to familiarize yourself with popular RL frameworks (like TensorFlow or PyTorch), brush up on mathematical concepts such as Markov Decision Processes, and practice implementing algorithms from academic papers. Collaboration with senior researchers and regular code reviews are also key aspects of the internship experience.

What is a Reinforcement Learning Internship?

A Reinforcement Learning Internship is a temporary position, often for students or recent graduates, where you work on projects involving reinforcement learning—a type of machine learning where agents learn by interacting with their environment to achieve goals. Interns typically assist with research, data analysis, algorithm development, and experimentation under the supervision of experienced professionals. This role provides hands-on experience with RL frameworks, coding in languages like Python, and exposure to real-world applications such as robotics, gaming, or autonomous systems. The internship helps build practical skills and can pave the way for advanced study or a career in artificial intelligence research.

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

To thrive as a Reinforcement Learning Intern, you need a strong background in mathematics (especially probability, statistics, and linear algebra), programming proficiency (commonly in Python), and foundational knowledge of machine learning concepts. Experience with libraries and frameworks such as TensorFlow, PyTorch, OpenAI Gym, and familiarity with relevant research papers or coursework are highly beneficial. Analytical thinking, creativity, and effective communication skills help interns solve complex problems and collaborate with research teams. These skills are crucial for contributing to innovative RL projects and efficiently learning from real-world experimentation.

What is the difference between Reinforcement Learning Internship vs Machine Learning Internship?

AspectReinforcement Learning InternshipMachine Learning Internship
Required SkillsReinforcement learning algorithms, Python, data analysisSupervised/unsupervised learning, Python, data preprocessing
Work EnvironmentResearch labs, AI startups, tech companiesTech firms, research institutions, data-driven companies
Industry UsageSpecialized in decision-making models and sequential learningBroader applications including classification, regression, clustering

Reinforcement Learning Internship focuses on decision-making algorithms and sequential learning, often in research or AI startup environments. Machine Learning Internship covers a wider range of algorithms and applications, suitable for various industries. Both roles require programming skills and a background in data science, but reinforcement learning internships are more specialized in AI decision systems.

More about Reinforcement Learning Internship jobs
What cities are hiring for Reinforcement Learning Internship jobs? Cities with the most Reinforcement Learning Internship job openings:
What are the most commonly searched types of Reinforcement Learning jobs? The most popular types of Reinforcement Learning jobs are:
What states have the most Reinforcement Learning Internship jobs? States with the most job openings for Reinforcement Learning Internship jobs include:
What job categories do people searching Reinforcement Learning Internship jobs look for? The top searched job categories for Reinforcement Learning Internship jobs are:
Reinforcement Learning Internship jobs near you
Infographic showing various Reinforcement Learning Internship job openings in the United States as of July 2026, with employment types broken down into 3% Internship, 73% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Research Internship - United States

Flexion Robotics

San Francisco, CA

Other

Vision

Posted 12 days ago

Job description

About Flexion:

At Flexion, we're building the intelligence layer powering the next generation of humanoid robots. Our mission is to accelerate the transition from fragile prototypes to real-world humanoid deployment. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zurich), and backed by leading international VC firms. In just months, we've gone from our first line of code to deploying real humanoid capabilities.
Fifty of the world's best robotics researchers are already building the future at Flexion's headquarters in Zurich. Among them are Nikita Rudin, David Hoeller, Julian Nubert, and Korrawe Karunratanakul -  scientists who have redefined what humanoid robots can do. Now we are building their counterpart team in the United States, in San Francisco.

The Role:

If you are among the most capable and ambitious early-career robotics researchers, someone who has stared at the limits of what robots can do today and decided that simply wasn't good enough, we want to hear from you.

You will join Flexion's US research team as an intern, take on research problems that matter most, and deploy real solutions on real hardware. You will work directly with a world-class team across two continents on challenges that have no published answers yet. This internship is designed to give exceptional graduate researchers the opportunity to do their highest-impact work in a fast-moving industrial research environment, with a clear path to a full-time Research Scientist role following the internship.

Requirements

Must-haves:

  • Ongoing PhD in Robotics, Machine Learning, or a closely related field, or a recently completed Master's degree with exceptional research output
  • Demonstrated experience deploying learning-based controllers on real robotic hardware, or strong research signal that you can do so quickly

Strong working knowledge in:

  • Reinforcement learning
  • Physics-based simulation (Isaac Gym/Lab, MuJoCo, or equivalent)
  • Python and PyTorch, including training neural networks at scale

Knowledge in at least two of the following:

  • Diffusion models
  • Flow matching
  • Dexterous manipulation
  • Sim-to-real transfer and real-to-sim calibration
  • Whole-body control and loco-manipulation
  • Synthetic data generation for robot learning
  • Vision Language Model Fine-Tuning (SFT and RL-based)
  • Transformer-based 3D Scene Understanding

Benefits

  • Competitive compensation package
  • A front-row seat at one of the world's most ambitious robotics companies
  • An energetic, collaborative team with a relentless bias for action
  • The opportunity to build something no one has ever done in this field -  alongside the world's leading researchers

Apply