Senior Machine Learning Engineer

Unity Technologies•Montreal, QC

40d•CA$136,100 - CA$220,600

About The Position

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. The AI models perform 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.

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. The AI models perform 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.