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Internship Deep Reinforcement Learning Jobs in Florida

University of Miami

Post Doctoral Associate

Coral Gables, FL · On-site

$46K - $63K/yr

Lead and contribute to research involving AI-powered and AI-enabled robotic systems, including deep reinforcement learning, computer vision, and human-robot interaction. * Facilitate strategic ...

University of Miami

Post Doctoral Associate

Coral Gables, FL · On-site

$46K - $63K/yr

... deep reinforcement learning, and human-machine interaction. Facilitate strategic collaborations across departments within the College of Engineering and with the UM Miller School of Medicine, to ...

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Internship Deep Reinforcement Learning information

What types of projects or tasks can I expect to work on during a Deep Reinforcement Learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in Deep Reinforcement Learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

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

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

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

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

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Internship Deep Reinforcement Learning jobs near you

Reinforcement Learning Engineering Intern

Persona AI

Pensacola, FL • On-site

$14.25 - $19/hr

Full-time, Internship

Posted 7 days ago

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!

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