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Reinforcement Learning Internship Jobs (NOW HIRING)

Prime Intellect

Internship

San Francisco, CA · On-site

$17.75 - $23.50/hr

We enable researchers, startups and enterprises to run end-to-end reinforcement learning at ... We're looking for exceptional interns who've already built real systems, contributed to open-source ...

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Reinforcement Learning Internship information

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How much do reinforcement learning internship jobs pay per hour?

As of Jul 3, 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.

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Reinforcement Learning Internship jobs near you

Graduate/PhD Research Intern, Machine Learning

Constellation Space

Seattle, WA • On-site

$6.0K - $7.0K/mo

Full-time

Posted 21 days ago

Be an early applicant

Job description

The Role

Constellation is seeking an ambitious Graduate or PhD Research Intern to join our Data Science / AI team. You will research and develop cutting-edge machine learning models to solve complex aerospace challenges, from predictive maintenance to autonomous orbital navigation.

Responsibilities

  • Conduct independent research to design and train novel machine learning architectures.

  • Analyze massive datasets derived from flight telemetry and satellite sensors.

  • Prototyping and testing algorithms in simulated aerospace environments.

  • Publish internal papers and present findings to the core engineering team.

Requirements

  • Currently pursuing a Master's or Ph.D. in Computer Science, Aerospace Engineering, Mathematics, or a related field.

  • Strong theoretical understanding of deep learning, computer vision, or reinforcement learning.

  • Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, or JAX).

  • Ability to work on-site in Seattle for the duration of the internship.