Machine Learning Engineer, Agentic Systems

As seen at CES 2026, Atlas is the robot that is transforming the role of humanoid robots in our world. This is your chance to come and work on the cutting edge of robotics, and make a direct impact on how people will interact with humanoids now and in the future. The Atlas Applications team is seeking an experienced Staff Machine Learning Engineer with expertise in building agentic systems.

In this pivotal role, you will work on System2 – the planning and reasoning layer that sits above robotic control – enabling humanoid robots to perform long horizon tasks in dynamic environments. You will work closely with behavior engineers to design and build Atlas’ agentic architecture – empowering robust autonomy through the use of task prompts, long‑horizon planning, VLM inference, memory, and tool use.

Candidates who have built advanced coding agents, autonomous research agents, or multi‑step reasoning systems are encouraged to apply. We are growing rapidly, building a commercial company that delivers cutting edge technology and solutions to our customers from industrial applications to logistics and warehouse solutions.

• 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.

• 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.
• Preferred experience working with robotics systems, vision models, and VLAs.
• Strong proficiency in Typescript, Python and/or C++, with comfort operating across large codebases.
• Knowledge and application of coding agents.
• History of pushing the state of the art through research, open‑source contributions, or novel production systems.

The base pay range for this position is $155,000 to $235,000 annually. Base pay will depend on multiple individualized factors including, but not limited to, internal equity, job‑related knowledge, skills and experience. Boston Dynamics offers a generous benefits package including medical, dental, vision, 401(k), paid time off and an annual bonus structure.