Senior Software Engineer - Machine Learning / Remote / Gaming/ MLOps

Job Description

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
  
  

Preferred Skills & Experience

• 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
  
  

What You Will Be Doing – Daily Responsibilities

• 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
  
  

Tech Breakdown

• 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
  
  

You Will Receive The Following Benefits

• Medical, Dental, and Vision Insurance
  
  

Applicants must be currently authorized to work in the U.S. on a full-time basis now and in the future.

Posted By: Maddie Hausberg