Senior ML Engineer, GenAI - Games

Netflix
USA - Remote2026-04-07onsite

About the job

We are looking for a Senior ML Engineer to bridge the gap between cutting-edge AI research and shipped game features. You will be a core technical contributor, responsible for implementing GenAI models into our production pipelines and game engines.

Responsibilities

Implementation & Integration: Lead the technical integration of GenAI tools and techniques into existing game engines (Unity/Unreal/Proprietary) and development workflows.

Feature Prototyping: Work directly with designers to build functional, AI-native gameplay mechanics—such as dynamic narrative systems, procedural asset generation, or intelligent NPC behaviors.

Optimization & Inference: Own the performance side of GenAI. You will optimize model latency and memory footprints to ensure AI features don't compromise game frame rates.

Pipeline Automation: Develop and maintain "AI superpower" tools for internal teams, such as automated texture generation, level design assistants, or code-completion agents.

Technical Mentorship: Provide guidance to mid-level and junior engineers on ML best practices, data privacy, and the ethical implementation of AI in creative spaces.

Bridge Research & Production: Translate complex AI research papers and open-source models into stable, production-ready code that aligns with our player experience goals.

Qualifications

Minimum

Game Development Background: 5+ years of experience in the games industry. You have a solid grasp of game loops, memory management, and what it takes to get a feature through a "Live Ops" cycle.

Practical GenAI/ML Experience: 3+ years of hands-on experience with Machine Learning/GenAI tools/techniques in a product-driven environment.

Software Engineering Excellence: Strong proficiency in languages like C++ and C#, with the ability to write clean, maintainable code within a large, complex codebase.

Infrastructure Familiarity: Experience with model fine-tuning, and managing the end-to-end ML lifecycle (data prep to deployment).

Problem Solver: You thrive in the "grey area" of emerging tech and can pivot quickly when a specific model or approach doesn't meet the needs of the game design.

Preferred

No preferred qualifications listed.