Senior Machine Learning Engineer

Build foundational agentic AI systems that bring goal-directed intelligence into the Unity engine. This onsite role in Mountain View, CA supports real-time games and simulations, with a focus on designing, scaling, and integrating AI agent models and systems for planning, memory and world modeling, and ML/AI safety. You will help shape Unity’s long-term agentic AI roadmap while mentoring engineers and researchers in a collaborative environment.

Compensation: USD 210,300 - 273,400 per year (gross pay annually).

Responsibilities

• Design, implement, and scale AI agent systems inside Unity environments that support goal-directed behavior, task planning and execution, and environment-aware decision-making.
• Develop reusable agentic frameworks that creators can extend, including planning modules, memory systems, and policy adaptation layers.
• Develop AI models for the Unity AI agentic system to perform tasks involved in building Unity games.
• Integrate machine learning models into real-time game engine constraints, optimizing for latency, compute, and determinism.
• Lead high-impact initiatives such as hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference frameworks for NPCs and simulations, and agent memory and world modeling for persistent, believable behavior.
• Collaborate across internal and external teams to enable innovative use cases in gaming, simulation, and interactive storytelling.
• Help drive Unity’s agentic AI vision and roadmap, ensuring modularity, usability, and performance across platforms.
• Establish best practices for model quality, simulation-based evaluation, and ML/AI safety in real-time systems.
• Mentor engineers and researchers while fostering a culture of innovation, excellence, and collaboration.

Requirements

• MS or Ph.D. in Computer Science, Machine Learning, Robotics (or equivalent practical experience).
• 5+ years of hands-on experience building ML systems in production, ideally in real-time or interactive environments.
• Strong background in one or more of the following: reinforcement learning, fine-tuning, decision-making under uncertainty, AI planning, or multi-agent systems.
• Ability to communicate in English for frequent and regular communication with colleagues and partners worldwide.

Benefits

• Comprehensive health, life, and disability insurance
• Commute subsidy
• Employee stock ownership
• Competitive retirement/pension plans
• Generous vacation and personal days
• Support for new parents through leave and family-care programs
• Office food snacks
• Mental Health and Wellbeing programs and support
• Employee Resource Groups
• Global Employee Assistance Program
• Training and development programs
• Volunteering and donation matching program

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