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Reinforcement Learning Game Jobs (NOW HIRING)

CD PROJEKT RED

$186.90K - $257K/yr

Familiarity with modelling human behaviour and Reinforcement Learning is a strong plus ... Familiarity with game engines and real-time simulations. * Intellectually curious. Humble and ...

A5 Labs

Our team focuses on building advanced AI agents through reinforcement learning, game-solving, fine-tuning, and planning, tackling challenges like anti-cheat detection and optimal gameplay.## What We ...

Nvidia

OR

... game AI, and physical simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo ... Experience in foundation and diffusion models, reinforcement learning, agent learning, and applied ...

Statheros

Develop and train reinforcement learning models for real-world applications, focusing on efficiency ... Experience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.

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How much do reinforcement learning game jobs pay per hour?

As of May 31, 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 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.

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.
Infographic showing various Reinforcement Learning Game job openings in the United States as of May 2026, with employment types broken down into 55% Full Time, 21% Part Time, 7% Temporary, 16% Contract, and 1% Summer. Highlights an 37% Physical, 37% Hybrid, and 26% Remote job distribution, with an average salary of $43,561 per year, or $20.9 per hour.
Senior Machine Learning Engineer, Reinforcement Learning - Egofold

Senior Machine Learning Engineer, Reinforcement Learning - Egofold

Snail Games USA

Beverly Hills, CA • On-site, Remote

$150K - $185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description

Senior Machine Learning Engineer, Reinforcement Learning – Egofold

About Snail Games USASnail Games strives to create the new high bar for gameplay experience in online gaming. We have been a global developer and publisher of digital entertainment since 2009 and are committed to pushing the boundaries of the industry.

About EgofoldEgofold is an AI initiative within Snail Games focused on intelligent agents, simulation, and AI-driven workflows for interactive products. It operates with startup-style speed and broad ownership, backed by an established game company, and is currently building practical prototypes while shaping its longer-term direction.

About the RoleWe are looking for a Senior Machine Learning Engineer with strong depth in machine learning and practical experience applying reinforcement learning and related methods to agent behavior and decision systems. This role is focused on the ML core of Egofold: designing experiments, training and improving models, shaping evaluation loops, and helping successful approaches become usable parts of the broader project.

This is not a siloed research role. The best candidates stay engaged through evaluation, iteration, and practical integration, and bring enough adjacent breadth to be effective in a small, collaborative team. We value curiosity, ownership, sound judgment, and respectful, low-ego collaboration.

Job Type: Full-TimeLocation: Hybrid – Los Angeles Area (1–2 in-office meetings per month)

Responsibilities

  • Design, train, and iterate on machine learning models for intelligent agents and decision-making systems, with an emphasis on reinforcement learning and related approaches.

  • Define and refine state representations, action spaces, reward structures, and evaluation criteria to improve agent behavior.

  • Build and improve practical experimentation and training workflows, including data generation, experiment tracking, and reproducibility.

  • Analyze results, debug model behavior, and make pragmatic tradeoffs between model performance, iteration speed, and system complexity.

  • Work closely with engineers and other partners to help integrate successful ML work into usable product systems.

  • Contribute thoughtful technical input on next-step experiments, tooling, and ML direction as Egofold continues to evolve.

Minimum Requirements

  • Strong foundation in machine learning, with hands-on experience building, training, and iterating on applied ML systems.

  • Professional or substantial project experience with reinforcement learning, agent-based systems, sequential decision-making, or closely related areas.

  • Strong Python skills and experience with modern ML frameworks such as PyTorch.

  • Experience designing experiments, evaluating model behavior, and improving results through systematic iteration.

  • T-shaped capability: deep machine learning expertise plus practical range across one or more adjacent areas such as simulation, evaluation, model integration, systems collaboration, or robotics-adjacent machine learning.

  • Strong problem-solving ability, sound judgment, and comfort working in ambiguous, fast-changing environments.

  • Respectful, low-ego collaborative style and willingness to work beyond a narrow specialty when the work requires it.

Nice to Have Any of the following are valuable, but we do not expect depth in every area:

  • Experience with reinforcement learning methods such as PPO, SAC, DQN, actor-critic, or related approaches.

  • Familiarity with simulation environments, multi-agent systems, game AI, or interactive agent behaviors.

  • Familiarity with C++, inference runtimes, or collaborating with engineers who deploy machine learning models into production systems.

  • Exposure to robotics, embodied AI, or embedded / on-device machine learning constraints.

Salary Range: $150,000 – $185,000 Annually

Why Join the Snail Games USA Team?

  • True focus on work/life balance

  • Paid company holidays, vacation, and separate sick leave

  • Medical, dental, vision, and Life/LTD

  • 401k with company match

Work Authorization Requirements

Applicants must be legally authorized to work in the United States at the time of application. This position does not offer visa sponsorship now or in the future (including H-1B).

Additional Information

As part of the Company’s activities in video game development, publishing, and short-form video content creation, certain projects, discussions, or creative materials may include themes, visuals, language, or subject matter that some individuals could find mature, violent, sexual, graphic, or otherwise sensitive in nature (collectively referred to as “Mature Content”). Examples may include, but are not limited to, depictions or descriptions of combat, violence, adult themes or relationships, suggestive or satirical humor, or strong language. Employees are expected to engage with such material in a professional and creative context as part of their job duties.