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 System 2 – 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.

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.

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.

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 between $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. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and a annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment. 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.

Staff Machine Learning Engineer, Agentic Systems