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Reinforcement Learning Engineer Jobs (NOW HIRING)

Rapidtrade

Senior Machine Learning Engineer

Manhattan, NY · On-site

$200 - $250/hr

You'll work on cutting-edge problems involving time-series forecasting, reinforcement learning, and ... Mentor junior engineers and contribute to engineering best practices * Research and evaluate new ML ...

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How much do reinforcement learning engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for reinforcement learning engineer in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 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.

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Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in the United States as of September 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 78% In-person, and 22% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.

Senior Deep Reinforcement Learning Engineer - Autonomous Driving

Santa Clara, CA

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

$122K - $168K/yr

Full-time

Posted 12 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

At NVIDIA, we are pushing the boundaries of what's possible within self-driving vehicle technology by bringing to bear the power of Deep Reinforcement Learning (RL). As a world leader in AI and high-performance computing, NVIDIA provides an outstanding platform where innovative research meets real-world production. We are looking for a Reinforcement Learning Engineer to join our mission in building intelligent, safe, and efficient self-driving technology that will redefine transportation on a global scale.

What you'll be doing:

  • Build and implement brand new Reinforcement Learning (RL) algorithms for autonomous vehicle decision-making and planning.

  • Develop and maintain scalable training pipelines and simulation environments for RL training.

  • Collaborate with perception, and planning teams to integrate RL models into the unified autonomous driving stack.

  • Benchmark RL model performance against imitation learning baselines in complex urban environments.

  • Optimize and deploy RL models to production-grade automotive hardware.

What we need to see:

  • BS or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or equivalent experience).

  • 12+ years of experieence in the related field.

  • Solid background in Reinforcement Learning, including policy gradient methods (PPO, GRPO), actor-critic architectures, on-policy and off-policy RL

  • Proficiency in PyTorch or TensorFlow and real experience with RL-related algorithm

  • Experience in C++ and Python development for real-time systems.

  • Strong analytical and problem-solving skills, with a track record of implementing and debugging complex RL systems.

Ways to stand out from the crowd:

  • Background in shipping autonomous driving features or embodied AI.

  • Experience with generative models (Flow Matching, Diffusion, or AR-based decoders) in the context of policy representation or trajectory modeling.

  • Experience with training policies on their own rollout distributions and handling the compounding error problems inherent in autonomous driving.

  • Experience working with large-scale data flywheels, including mining scenarios from fleet telemetry logs, auto-labeling pipelines, and automated performance tracking.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 31, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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