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Reinforcement Learning Engineer information

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$28.4K

$86.6K

$143.1K

How much do reinforcement learning engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for reinforcement learning engineer in Florida is $86,585.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $113,200.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

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

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What are some common challenges faced by Reinforcement Learning Engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

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

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Florida? For Reinforcement Learning Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Florida look for? The top searched job categories for Reinforcement Learning Engineer jobs in Florida are:
What cities in Florida are hiring for Reinforcement Learning Engineer jobs? Cities in Florida with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Florida as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $86,585 per year, or $41.6 per hour.

Reinforcement Learning Engineering Intern

Persona AI

Pensacola, FL • On-site

$14.25 - $19/hr

Full-time, Internship

Re-posted 19 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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