Senior Software Engineer - Machine Learning / Remote / Gaming/ MLOps
- Los Angeles, CA
- Contract
- Full-time
This is a full-time, 12-month contract role with a leading global video game developer and publisher, renowned for creating competitive, genre-defining multiplayer titles. The company fosters a collaborative, player-focused culture where cutting-edge technology meets immersive gameplay. You will join a specialized machine learning engineering team that builds large-scale ML systems to enhance competitive gameplay experiences. This role offers the opportunity to work on a major fighting game title ahead of its launch, developing advanced AI systems that challenge and engage players.
The position is fully remote within the U.S., with occasional on-site visits for whiteboarding sessions or key collaboration points. Flexible hours are available to accommodate project needs, with a focus on delivering high-quality, scalable ML solutions in a fast-moving game development environment.
Contract Duration: 12 months (possibility to convert to full-time)Required Skills & Experience
- Proven experience delivering large-scale, end-to-end ML systems
- Strong infrastructure skills, particularly in MLOps with an AI/ML perspective
- Proficiency in at least one of the following: Java, C++, Python, C#, or SQL
- 2+ years’ experience with ML pipelines and common tooling such as MLflow
- Familiarity with PyTorch or TensorFlow
- Experience working with or designing large-scale LLM systems
- Bachelor’s degree in Computer Science or related field
- 2–3 years of applied machine learning experience
- Background or strong interest in the gaming industry
- Exposure to reinforcement learning (selling point, not required for interview)
- Familiarity with Unreal Engine
- Comfort with large, complex programming challenges and systems
- Design, develop, and optimize ML systems that directly enhance in-game AI behavior for a competitive fighting game
- Implement reinforcement learning–based policies to improve gameplay experiences and provide advanced training tools for players
- Collaborate with game engineers, researchers, and product managers to integrate ML models into core gameplay systems
- Build and maintain ML pipelines, ensuring scalability and performance for launch-ready systems
- Work closely with the ML Pods team to deliver high-quality AI features under tight timelines
- Troubleshoot, refine, and iterate on ML systems to meet competitive gameplay standards
- 50% ML system design and optimization (ML pipelines, reinforcement learning, LLM integration)
- 30% Infrastructure and MLOps (scaling, deployment, orchestration)
- 20% Collaboration with game engineering, research, and product teams
- Medical, Dental, and Vision Insurance