ZipRecruiter

Log In

1

Reinforcement Learning Engineer Jobs in Florida (NOW HIRING)

TAIT

Learning eXperience Designer (LXD)

Orlando, FL · On-site +1

... precision engineering, and creative design. TAIT's 20 global offices have developed iconic ... Define learning objectives and design experiences, activities, assessments, and reinforcement ...

Tait

Learning eXperience Designer (LXD)

Orlando, FL · On-site

... precision engineering, and creative design. TAIT's 20 global offices have developed iconic ... Define learning objectives and design experiences, activities, assessments, and reinforcement ...

Deloitte

AI and Data Science Engineer II

Miami, FL

$109K - $131K/yr

Experience with deep learning architectures or reinforcement learning The wage range for this role ... We are a team of strategists, data scientists, operators, creatives, designers, engineers, and ...

Deloitte

AI and Data Science Engineer II

Tampa, FL

$108K - $129K/yr

Experience with deep learning architectures or reinforcement learning The wage range for this role ... We are a team of strategists, data scientists, operators, creatives, designers, engineers, and ...

previous page

Showing results 41-60

All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Florida

Reinforcement Learning Engineer information

See Florida salary details

$28.4K

$86.6K

$143.1K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 15, 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:

Infographic showing various Reinforcement Learning Engineer job openings in Florida as of September 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $86,585 per year, or $41.6 per hour.

Software Engineer Intern | Spring | Autonomous Intelligent Sensing for Space Applications

Sarasota, FL • On-site

MRSL Real-Time Systems Laboratory Inc
Guided Missile and Space Vehicle Manufacturing • 11 - 50 employees
Learn more about MRSL Real-Time Systems Laboratory Incexternal

Full-time, Internship

Posted 6 days ago

Job description

Mission and Opportunity MRSL is a world-class developer of advanced signal processing, intelligent sensing, and autonomous systems for the U.S. Government. We build software and algorithms that help complex systems perceive, understand, and respond intelligently to their environment

Our technologies are deployed across a broad range of intelligence and defense applications-including this project focusing on the emerging domain of autonomous space systems-where reliable, mission-critical autonomy can make the difference between success and failure. You'll work hand-in-hand with our senior engineers from day one-no toy problems, no throwaway side project. You'll take ownership of meaningful technical work on a real, space-bound system and help drive it through its next critical stages.

The system is being prepared for an upcoming launch and currently runs in a live virtual environment-exercised on target hardware and mission emulation as if operating on orbit. The next phase continues that work through algorithm and model development, testing, performance assessment, and iterative improvement ahead of flight. What You Will Do You'll help mature the autonomy software in a live, mission-realistic virtual environment as we prepare it for flight: Collaborate with experienced engineers on system design and production-quality software development.

Extend intelligent sensing, autonomy, and decision-making capabilities using modern software and AI techniques. Tune, evaluate, and optimize machine learning and reinforcement learning models. Perform model validation, system verification, and end-to-end mission testing on target GPU hardware.

Support pre-launch integration, readiness, and validation of autonomous sensing software. Design, test, and validate remote system updates, monitoring, metrics, and dashboards. Analyze sponsor feedback, anomalies, and system issues to identify root causes and develop resolutions.

Document findings, communicate results, and translate lessons learned into improved operational capability. Who We Are Looking For We are looking for an engineering intern who is driven and excited by difficult technical problems. The strongest candidates will be comfortable learning quickly, working independently when needed, and contributing as part of a multidisciplinary engineering team.

Working toward or already holding a B.S. or graduate degree in Electrical Engineering, Computer Engineering, Computer Science, Aerospace Engineering, Physics, Imaging Science, or a related engineering or science discipline. Strong experience with programming in some combination of Python, C/C++, Java, scripting, and Linux

Ability to reason through algorithmic and system-level problems and implement practical solutions in code. Strong communication skills, attention to detail, and a willingness to take ownership of assigned work. Bonus Experience ML, RL, agentic AI, PyTorch, TensorFlow, Keras, scikit-learn, or Edge ML Autonomous or real-time sensing systems, embedded processing, or sensor fusion Signal or image processing, detection and estimation, classification, or spectral analysis ROS 2, robotics middleware, or distributed systems Docker, Git workflows, CI/CD, automated testing, and software validation Space systems, flight software, or operations involving embedded or real-time constraints Why This Internship Is Different Real mentorship - you work shoulder-to-shoulder with senior engineers, not parked on an isolated side project.

A path to a career - most of our entry-level engineers are hired out of this internship program, and interns who excel and are a good fit are often given a full-time offer. Real-world mission - experience development, validation, and launch preparation in a single term, on a system headed for flight. Eligibility and Internship Details This is a paid, full-time internship (40 hours per week, on-site) available during the Spring term at MRSL's Sarasota, Florida office.

Housing allowance is provided.Intern candidates must be U.S. citizens and able to meet TS/SCI clearance eligibility requirements.We have a strong preference for intern candidates who will still be in school for two semesters after the internship ends, whether finishing an undergraduate degree, or starting or continuing graduate work. This allows us to extend offers to selected candidates at the end of the internship so that their clearance is done by the time they graduate

**Will begin reviewing candidates Mid-October.

Apply