Machine Learning Engineer, Large Scale Behavior Cloning

Boston Dynamics•Waltham, MA

17d

About The Position

As seen at CES 2026, Atlas is the humanoid robot transforming what's possible in real-world manipulation and mobility. Our behavior development process is built on repeated iteration between data collection, policy training, hardware evaluation, and targeted diagnostics. We are seeking a Machine Learning Engineer to build the tools and infrastructure that power this cycle end to end. Your scope will span data pipelines, training infrastructure, evaluation systems, and the tooling that connects them, with the goal of reducing friction and increasing the throughput and quality of each iteration. You will work in close collaboration with research scientists, ML engineers, data operations teams, and robot demonstrators.

Requirements

A Bachelor's degree in Computer Science, Robotics or related field, and 3+ years of experience developing software for robotics, ML infrastructure, or related fields.
Strong proficiency in Python, familiarity with C++
Experience building internal tools, dashboards, or GUI applications.
Familiarity with ML workflows including training pipelines, experiment tracking, and dataset management.
Experience with data analysis and visualization.
Experience with cloud infrastructure, databases, Docker, and job orchestration.
Strong communication and collaboration skills.

Nice To Haves

MS in Robotics, Computer Science, Machine Learning, or a related field.
Familiarity with behavior cloning, diffusion policies, or VLA/VLM architectures.
Experience with simulation environments (MuJoCo, Isaac Sim, or similar).
Prior experience building or contributing to evaluation pipelines for ML or robotics systems.

Responsibilities

Actively participate in ongoing R&D initiatives, collaborating closely with Research Scientists and Infrastructure Engineers.
Develop tools to query and gain insights into data, training, and testing performance metrics.
Analyze and track failures in experimental robot runs.
Work with robot simulation software to develop scenarios, tests, and data collection tools.
Build internal tools and platforms that accelerate the collect, train, and evaluate loop.
Develop software that gives researchers and engineers immediate visibility into policy performance, data quality, and collection gaps.
Work across hardware and simulation environments to support evaluation and rapid experimentation.
Maintain and improve the code repository, ensuring its ongoing maintenance and improvement to meet evolving needs (CI/CD, testing, deployment).