Staff Machine Learning Engineer, Agentic Systems

Job description

Job responsibilities

• Design and implement System 2 architectures for humanoid robot control, including planning, reasoning, memory, and tool-use frameworks.
• Develop logging, observability and evaluation methodologies to guide performance improvement and measure reasoning quality, safety, reliability, and generalization.
• Collaborate cross-functionally with behavior, controls, perception, and product teams to ship end-to-end capabilities.
• Engage with customers and internal stakeholders to understand real-world use cases and ensure solutions are practical, reliable, and impactful.
• Stay at the forefront of agentic research and translate state-of-the-art techniques into production systems.
• Contribute to a strong engineering culture through code reviews, testing, documentation, and thoughtful system design.

Job requirements

• 5+ years of professional software engineering experience, including significant work on LLM-driven or agentic systems.
• Hands-on experience building or deploying agentic architectures (e.g., coding agents, tool-using LLM systems, autonomous task agents).
• A track record of improving agentic system performance through evaluation and benchmarking.
• Strong fundamentals in data structures, algorithms, distributed systems, and software architecture.
• Demonstrated ability to ship reliable, maintainable, and well-tested software.
• Ability to reason about safety, failure modes, and robustness in autonomous systems.