Senior Machine Learning Engineer

About the role

The Senior Machine Learning Engineer will lead the development of foundational AI systems within the Unity engine, enabling creators to build smarter, more responsive in-game agents and simulations. This role involves designing, implementing, and scaling AI agent systems, developing reusable agentic frameworks, and integrating machine learning models within real-time game engine constraints.

Responsibilities

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

Requirements

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Robotics, or a related field—or equivalent practical experience.
• 5+ years of hands-on experience developing ML systems in production, ideally within 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.

Qualifications

• Gross pay annually: $210,300 - $273,400 USD.
• Benefits include comprehensive health, life, and disability insurance, commute subsidy, employee stock ownership, competitive retirement/pension plans, generous vacation and personal days, support for new parents, office food snacks, mental health and wellbeing programs, employee resource groups, global employee assistance program, training and development programs, and volunteering and donation matching program.

Skills

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Robotics, or a related field.
• Experience developing ML systems in production, preferably within real-time or interactive environments.
• Knowledge of reinforcement learning, fine-tuning, decision-making under uncertainty, AI planning, or multi-agent systems.

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.

Pay

Gross pay annually: $210,300 - $273,400 USD.

Schedule

Not specified.