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

Position Overview

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, and flexible hours to accommodate project needs. Contract Duration: 12 months (possibility to convert to full-time)

Key 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 and troubleshoot, refine, and iterate on ML systems to meet competitive gameplay standards

Required Qualifications

• 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 Qualifications

• 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 (a selling point, not required for interview)
• Familiarity with Unreal Engine
• Comfort with large, complex programming challenges and systems

Benefits & Perks

• Medical, Dental, and Vision Insurance