Senior Machine Learning Engineer, Unity

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field
• 5+ years of hands-on experience developing ML systems in production, ideally within real-time or interactive environments
• Experience with multi-agent systems, orchestration, or AI tool integration
• Strong background in one or more of the following: LLM, reinforcement learning, decision-making under uncertainty, AI planning, or multi-agent systems
• Proficiency in at least one general-purpose programming language (e.g., Python, C++, Go, Java) and familiarity with ML frameworks (e.g., PyTorch, TensorFlow)
• Strong system design skills and the ability to architect performant, scalable ML systems
• Excellent communication and collaboration skills; ability to work effectively with cross-functional teams including engine developers, designers, and product managers
• Experience with behavior trees, utility AI, or hierarchical task planning
• This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English

Desirable

• We’re looking for a Staff Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-game agents and simulations
• Your work will directly drive innovation, allowing developers and designers to integrate sophisticated AI behavior seamlessly into their worlds
• This role is perfect for someone passionate about pushing the boundaries of AI, multi-agent systems, reinforcement learning, and intelligent decision-making in complex, real-time environments
• Design, implement, and scale AI agents that assist in generating game code and executing goal-directed behaviors
• Define orchestration logic for single- and multi-agent systems
• Develop reusable agentic frameworks - planning modules, memory systems, or policy adaptation layers - for creator extensibility
• 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