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How much do reinforcement learning engineer jobs pay per year?

As of Aug 19, 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 is a reinforcement learning engineer?

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 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 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 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 August 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $86,585 per year, or $41.6 per hour.

Robotics Simulation Engineer

Persona AI

Pensacola, FL • On-site

Other

Re-posted 14 days ago

Job description

We're looking for a Simulation Engineer to own and expand our NVIDIA Isaac Sim and Omniverse simulation infrastructure. You'll build the digital twin environments, sim assets, and CI/CD pipelines that our autonomy team relies on daily. You will help achieve the vision in which every robot behavior we develop is prototyped, tested, and validated in simulation before it runs on hardware.
As a simulation engineer at Persona, you will have an incredible opportunity to shape the simulation infrastructure that underpins our entire autonomy stack. You will report to the Behavior Coordination Lead and work closely with machine learning, locomotion, manipulation, perception, and devops teams.
Your Role:
  • Build, maintain, and extend simulation environments in NVIDIA Isaac Sim and Omniverse for humanoid robot development.
  • Develop and manage OpenUSD sim assets: robot models, tools, workpieces, customer facility environments (shipyards, steel fabrication plants, industrial sites).
  • Create and maintain physics-accurate digital twins of customer facilities (shipyards and industrial manufacturing) for behavior validation and deployment planning.
  • Integrate all autonomy subsystems (locomotion, manipulation, perception, hands, navigation, welding) to run against Isaac Sim.
  • Design and implement behavior-level CI/CD pipelines that automatically validate robot behaviors in simulation.
  • Prototype and mock-test robot behaviors (welding, navigation, manipulation) in simulation before hardware integration.
  • Develop synthetic data generation pipelines for training perception, manipulation, and navigation models.

We're Looking For:
  • BS, MS, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field.
  • 3+ years of professional experience in robotics simulation, digital twin development, or physics-based simulation environments.
  • Strong hands-on experience with NVIDIA Isaac Sim and/or NVIDIA Omniverse.
  • Working knowledge of OpenUSD (Universal Scene Description): authoring, composition, referencing, flattening, and debugging USD stage hierarchies.
  • Proficiency in Python; comfortable writing simulation tooling, test harnesses, and automation scripts.
  • Experience with at least one physics engine: PhysX, MuJoCo, Bullet, or Drake.
  • Solid understanding of robot kinematics, dynamics, and articulated body simulation.
  • Experience developing or maintaining CI/CD pipelines for simulation or robotics software.
  • Familiarity with containerization (Docker) and DevOps practices for simulation infrastructure.
  • Ability to create and manage 3D simulation assets (meshes, materials, collision geometry, articulation definitions).

Preferred or Bonus Qualifications:
  • Experience with NVIDIA Isaac Lab for reinforcement learning environment setup and training.
  • Familiarity with NVIDIA Cosmos for synthetic data generation and scene variability.
  • Experience with ROS/ROS 2 and Gazebo simulation.
  • Experience with Unreal Engine or other real-time rendering engines for robotics visualization.
  • Background in manipulation simulation: contact modeling, grasp planning, dexterous multi-fingered hand interaction, and force/torque estimation.
  • Experience with motion capture data pipelines and motion retargeting to robot models.
  • Exposure to behavior trees, task planning, or autonomy stack architecture.
  • Knowledge of Omniverse extensions development and Kit SDK.

Apply