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NEXTMOVEFDE careers · United States
Boston Dynamics

Staff Machine Learning Engineer, Agentic Systems

AI summary of the role

This role designs and builds the System 2 planning and reasoning layer for Atlas humanoid robots, enabling long-horizon autonomous tasks.

What you’ll do

  • 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.

What you’ll bring

  • 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.

Technologies

LLM · agentic systems · VLM · tool use · memory · planning · reasoning · Typescript · Python · C++

About Boston Dynamics

Designs and manufactures advanced mobile robots (Spot quadruped, Stretch box-handler, Atlas humanoid) for industrial inspection, warehouse logistics, and factory automation.

Acquired · 1000–2000 people

Source and classification

Production engineering · Evidence for this classification:

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
How jobs are selected

Employer postings · Data from · Sources