Senior Staff ML Engineer - Robotics & Agentic Systems

Aimlroles; Waltham (MA); On-site; USD 180,000 - 220,000; Full time

Job summary

Boston Dynamics is seeking a versatile full stack engineer to build and integrate the systems that enable Atlas to perform complex tasks in dynamic environments.

You will work across the agentic stack, from harness design to context engineering and benchmarking, partnering with ML engineers, product teams, and interaction designers to develop planning and reasoning systems and integrate them with appropriate tools and prompts.

Qualifications

• 5+ years of professional software engineering with full stack background spanning backend and LLM integrations.
• Ability to design and integrate APIs and third-party services in complex distributed systems.

Responsibilities

• Work directly on Atlas' agentic capabilities, utilizing VLMs, tool calls, context engineering, and memory to support multiple real-world applications.
• Design and implement observability, logging, and tracing infrastructure to provide visibility into system behavior and performance.
• Develop and utilize evaluation and benchmarks to measure reasoning quality, safety, reliability, and generalization across tasks and environments.
• Develop the operator dashboards, task configuration UIs, and diagnostic interfaces to help users build and deploy Atlas applications.
• Collaborate cross-functionally with behavior, controls and product experts 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.
• Contribute to a strong engineering culture through code reviews, testing, documentation, and thoughtful system design.

Skills

Full stack engineering

LLM integration

API design

Distributed systems

Backend: TypeScript

Backend: Python

Code quality

Job description

Boston Dynamics is seeking a versatile full stack engineer to build and integrate the systems that enable Atlas to perform complex tasks in dynamic environments.

You will work across the agentic stack, from harness design to context engineering and benchmarking, partnering with ML engineers, product teams, and interaction designers to develop planning and reasoning systems and integrate them with appropriate tools and prompts.