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Summer Reinforcement Learning Intern Jobs (NOW HIRING)

College Intern

Clearwater, FL · On-site

$13.75 - $18.50/hr

Summer 2026 College Intern- Organizational Development & Learning (OD&L): Our OD&L team partners across BayCare to build a culture of continuous learning, leadership development, and organizational ...

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Summer Reinforcement Learning Intern information

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$8

$17

$24

How much do summer reinforcement learning intern jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for summer 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 types of projects or tasks can I expect as a Summer Reinforcement Learning Intern?

As a Summer Reinforcement Learning Intern, you can expect to work on projects ranging from implementing and testing RL algorithms to analyzing experiment results and optimizing model performance. Interns often collaborate with experienced researchers and engineers, contributing to both independent and team projects. You may also be involved in literature reviews, setting up simulation environments, and presenting findings to your team. The role provides hands-on experience with real-world RL applications, and you’ll have the opportunity to learn from feedback and mentorship throughout your internship.

What is the difference between Summer Reinforcement Learning Intern vs Summer Data Science Intern?

AspectSummer Reinforcement Learning InternSummer Data Science Intern
Required CredentialsUndergraduate or graduate in CS, AI, or related fields; some knowledge of machine learning and programmingUndergraduate or graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentResearch-focused, experimental projects, often in AI and machine learning teamsData analysis, modeling, visualization, and reporting tasks across various departments
Employer & Industry UsageTech companies, AI startups, research labsTech firms, finance, healthcare, and consulting industries

The Summer Reinforcement Learning Intern role focuses on developing and testing reinforcement learning algorithms, often within AI research teams. In contrast, the Summer Data Science Intern role involves broader data analysis and modeling tasks. Both roles require programming skills and are common in tech industries, but they differ in their specific focus and project types.

What are Summer Reinforcement Learning Interns?

Summer Reinforcement Learning Interns are students or recent graduates who work temporarily, usually during the summer, to gain hands-on experience in reinforcement learning, a subfield of machine learning. Their responsibilities often include assisting with the development and testing of algorithms, analyzing data, and collaborating with research teams on projects related to artificial intelligence. This role provides an opportunity to apply theoretical knowledge from coursework to real-world problems, often resulting in valuable skills and networking opportunities for future careers in AI or data science.

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

To thrive as a Summer Reinforcement Learning Intern, you need a solid background in computer science, mathematics (particularly probability and linear algebra), and experience with machine learning frameworks. Familiarity with Python, TensorFlow or PyTorch, and a strong grasp of reinforcement learning algorithms are typically required, often supported by coursework or relevant certifications. Strong problem-solving skills, curiosity, and effective communication help you stand out in collaborative research and fast-paced project environments. These skills are crucial for contributing to innovative AI projects, rapidly learning new concepts, and effectively sharing findings with mentors and team members.
More about Summer Reinforcement Learning Intern jobs
What cities are hiring for Summer Reinforcement Learning Intern jobs? Cities with the most Summer Reinforcement Learning Intern job openings:
What states have the most Summer Reinforcement Learning Intern jobs? States with the most job openings for Summer Reinforcement Learning Intern jobs include:

Reinforcement Learning Engineering Intern

Persona AI

Pensacola, FL • On-site

$14.25 - $19/hr

Full-time, Internship

Re-posted yesterday


Job description

Reinforcement Learning Engineering Intern
Location: Downtown Pensacola, FL
Type: Full-time Internship, 40 hours/week
About the Internship
The Reinforcement Learning Engineering Internship is an opportunity for Bachelors and Masters candidate students to join and contribute to the Persona team as we develop our industrial humanoids. Our objective is to provide each intern with a positive learning environment, hands-on experience with humanoids, and ownership over their own project direction. We are looking for students with an excitement for learning, technical excellence, and creative problem-solving skills.
Each intern will have a designated mentor to provide guidance and assistance in developing and making progress towards a target goal. We have a strong bias for projects that lead to software, controls, or policies deployed on our hardware and extending the capabilities of our systems. Projects will be jointly planned by the intern and their mentor to build on the intern's background, extend their experience to new areas of interest, and fit into the broader goals of the Persona reinforcement learning team.
Role Description
For this role, the specific tasks will be defined prior to the start date by the mentor and the intern based on their experience, proficiency, and personal interests. The scope may also be adjusted to fit the project within the intern's time-frame. We encourage interns to share their interests even if they may be entirely different from their technical background. Some example general tasks that may be a part of any project are described below:
  • Develop new simulation training environments
  • Design new behaviors or extend capabilities for the Persona robots
  • Deploy to hardware, log data, and analyze results
  • Create or implement new algorithms for modeling, training, sensing, or deployment
  • Characterize hardware sensors, actuators, and general robot parameters
Qualifications
  • Current Undergraduate or Masters student
  • Software proficiency in Python, C/C++, Java, or Rust
  • Experience with basic machine learning concepts
Bonus Experience
  • Worked with Pytorch or similar
  • Physics simulator experience such as IsaacLab/IsaacSim, Mujoco, or similar
  • Deployed controls software to robot hardware
  • Trained policies with reinforcement learning
  • Worked with motion diffusion models or VLAs
  • Experience with character animation
  • Worked on vision or localization
Open Technical Areas
  • Perception
  • Locomotion
  • Manipulation
  • Motion Planning
  • Imitation Learning
  • Motion Retargeting
  • Sim-to-Real Modeling
Application Timeline
We are accepting applications on a rolling basis. We will interview and make offers for upcoming intern cohorts until we fill all openings. We will close the application process for an upcoming cohort approximately 3 months before the start of the cohort and recommend applying approximately 6 months in advance.
Note: we are no longer accepting applications for Fall 2026.
The interview process we are currently following involves two interviews. First, a phone pre-screen with a member of our staff. Second, a presentation and discussion interview with one to two of our engineers. The presentation is meant to be informal and give an opportunity for you to share your background, experiences, and interests. We like the chance to see pictures and videos of your projects and hear what part of robotics excites you most! We will also give an overview of the work we are doing here at Persona AI and leave time for you to ask us questions.
We aim to get back to you as soon as we can but it may take a few weeks, especially in between cohorts. Please know we are working on it and will get back to every application!