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Reinforcement Learning Game Jobs (NOW HIRING)

Medal

World Model / Action Policy Researcher

New York, NY · On-site

$350K - $450K/yr

What We're Looking For * 5+ years of experience in deep learning research or reinforcement learning ... Gaming & simulation passion: Interest in interactive environments, physics-based simulations, or ...

Quantiply Corporation

Data Scientist

San Jose, CA · On-site

... game theory or other technical field. * Strong knowledge of mathematics. * Strong knowledge of ... Strong knowledge of deep learning. * Strong knowledge of reinforcement learning. * Strong ...

Quantiply Corporation

Data Scientist

San Jose, CA

... game theory or other technical field. * Strong knowledge of mathematics. * Strong knowledge of ... Strong knowledge of deep learning. * Strong knowledge of reinforcement learning. * Strong ...

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Reinforcement Learning Game information

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How much do reinforcement learning game jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for reinforcement learning game in the United States is $20.94, according to ZipRecruiter salary data. Most workers in this role earn between $14.18 and $23.80 per hour, depending on experience, location, and employer.

What is a Reinforcement Learning Game?

A Reinforcement Learning (RL) Game is a simulation or environment designed for testing and training artificial intelligence (AI) agents using reinforcement learning techniques. In these games, an agent interacts with the environment by taking actions and receiving rewards based on its performance, allowing it to learn optimal strategies over time. RL games are widely used in research to benchmark algorithms and in industry to develop intelligent behaviors for robots, automated systems, or video game characters. Popular RL games include OpenAI Gym environments, Atari games, and custom simulations built for specific tasks.

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

To thrive as a Reinforcement Learning Engineer in game development, you need a strong background in machine learning, algorithms, and programming (typically Python), often supported by a degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and RL-specific libraries (such as OpenAI Gym or Unity ML-Agents), as well as experience with simulation environments, is typically required. Critical thinking, creativity, and effective communication help you design innovative AI solutions and collaborate with interdisciplinary teams. These skills are crucial for developing intelligent game agents that enhance player experience and drive technological advancement in interactive entertainment.

How does a Reinforcement Learning Game Engineer typically collaborate with game designers and data scientists during development?

As a Reinforcement Learning Game Engineer, you will frequently collaborate with game designers to integrate RL agents in ways that enhance gameplay and balance. Close coordination with data scientists is also common, as they help analyze agent behaviors and performance data to refine training environments and reward structures. Regular cross-functional meetings and iterative testing sessions are standard, ensuring that RL-driven features both align with the game's vision and deliver measurable improvements. This collaborative environment fosters innovation and provides valuable insights into both AI and game design best practices.
Infographic showing various Reinforcement Learning Game job openings in the United States as of June 2026, with employment types broken down into 8% As Needed, 68% Full Time, 21% Part Time, 1% Temporary, and 2% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $43,561 per year, or $20.9 per hour.

Senior Software Engineer, Simulation Systems

Bot Auto

Houston, TX • On-site, Remote

Other

Posted 6 days ago

Job description

Senior Software Engineer, Simulation Systems

Houston, TX or San Francisco Bay Area

About the Role

We are building the next generation of autonomous trucking technology to make freight transportation safer, more efficient, and more scalable.

Our Simulation team develops the virtual environments, testing infrastructure, and AI-driven simulation systems that enable rapid development and validation of autonomous driving software. We leverage large-scale simulation, synthetic data generation, reinforcement learning environments, and emerging world-model technologies to accelerate autonomy development.

We are seeking a software engineer with strong C++ expertise and a passion for building scalable simulation systems. This role offers the opportunity to work at the intersection of autonomous driving, simulation, robotics, and AI.

Build Autonomous Driving Simulation Systems
  • Design and develop high-performance simulation infrastructure for autonomous vehicle development and validation
  • Build scalable systems for scenario generation, simulation execution, and evaluation
  • Develop simulation tooling used by Perception, Prediction, Planning, and Controls teams
  • Improve simulation realism, scalability, and operational efficiency
  • Collaborate across teams to support testing, validation, and development workflows
Develop AI-Driven Simulation Capabilities
  • Build infrastructure supporting reinforcement learning and closed-loop evaluation workflows
  • Develop systems for synthetic data generation and automated scenario creation
  • Collaborate with ML engineers and researchers to integrate learned models into simulation environments
  • Explore emerging approaches in world modeling, agent simulation, and Physical AI
Engineering Excellence
  • Write production-quality C++ and Python code
  • Participate in architecture and technical design discussions
  • Build reliable, maintainable, and well-tested systems
  • Contribute to code reviews and engineering best practices
  • Create clear technical documentation for systems and tools
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field
  • 3+ years of professional software development experience
  • Strong expertise in modern C++ (C++17 or newer preferred)
  • Experience designing and developing production software systems
  • Strong understanding of:
    • Multithreading and concurrency
    • Memory management
    • Performance optimization
    • Software architecture and system design
  • Experience working with simulation, robotics, gaming, or autonomous systems
Preferred Qualifications
  • Experience with simulation platforms such as:
    • CARLA
    • Isaac Sim
    • Unreal Engine
  • Familiarity with reinforcement learning concepts and workflows
  • Experience with agent-based simulation or closed-loop simulation systems
  • Experience building synthetic data generation pipelines
  • Experience with ROS or ROS2
  • Experience with cloud-native infrastructure such as Docker, Kubernetes, AWS, or GCP
  • Familiarity with machine learning infrastructure and large-scale data processing systems
Nice to Have
  • Experience in autonomous driving or robotics applications
  • Experience with multi-agent simulation systems
  • Familiarity with world models, generative simulation, or Physical AI technologies
  • Experience with sensor simulation, including camera, lidar, or radar
  • Experience with physics engines and real-time systems
  • Experience with CUDA, OpenGL, Vulkan, or graphics programming
What We're Looking For
  • Strong software engineering fundamentals
  • Systems-thinking mindset and attention to detail
  • Curiosity about simulation, AI, robotics, and autonomous systems
  • Ability to work across simulation, infrastructure, and machine learning domains
  • Comfortable working in a fast-paced environment with evolving technical challenges
  • Passion for building the next generation of intelligent simulation platforms

Apply