Lead the development of foundational agentic AI systems inside the Unity engine, shaping models and tools for real-time games and simulations.

Design, build, and scale AI agent systems in Unity environments for goal-directed behavior, task planning and execution, and environment-aware decision-making.
Create reusable agentic frameworks (for example: planning modules, memory systems, or policy adaptation layers) that creators can extend in their own projects.
Develop AI models for Unity’s AI agentic system to support a range of tasks used to build Unity games.
Integrate ML models into real-time game engine constraints by optimizing for latency, compute, and determinism.
Drive high-impact initiatives, including:
- Hierarchical reinforcement learning for scalable behaviors.
- AI planning and goal inference frameworks for NPCs and simulations.
- Agent memory and world modeling systems for persistent, believable behavior.
Partner with internal and external teams to enable new use cases across gaming, simulation, and interactive storytelling.
Shape Unity’s long-term agentic AI roadmap by ensuring modularity, usability, and performance across platforms.
Define and advocate best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.
Mentor engineers and researchers while building a technical culture focused on innovation, excellence, and collaboration.

MS or Ph.D. in Computer Science, Machine Learning, Robotics (or equivalent practical experience).
5+ years of hands-on experience developing ML systems in production, ideally in real-time or interactive environments.
Strong foundation in one or more areas including:
- Reinforcement learning.
- Fine-tuning.
- Decision-making under uncertainty.
- AI planning.
- Multi-agent systems.

Requires frequent and regular communication with colleagues and partners worldwide whose common language is English.

Senior Machine Learning Engineer

Job Description