Senior ML Engineer, GenAI - Games

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

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. You won’t just be prompted with ideas; you’ll be building the infrastructure and logic that brings those ideas to players.

Key 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

• 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.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.