We are seeking a highly experienced and motivated ML Engineer to join our Stretch Grasping Intelligence team. In this pivotal role, you will help develop novel AI algorithms to solve real-world mobile perception and manipulation problems. A strong background in deep learning methods for robotics, such as Reinforcement Learning, VLA models, and/or behavior cloning, is highly desirable for success in this position. You will work on techniques that tightly couple perception to robot behavior and planning and produce efficient and robust policies. You will be instrumental in building solutions that we can deliver to our customers. You will collaborate closely with software, controls, and hardware teams to rapidly test, iterate, and deploy your algorithms on robot. You will work with other leaders on the project to maximize the capabilities of the Stretch robot.
Our team is responsible for enabling the Stretch robot to intelligently manipulate objects in warehouse environments. We also develop and maintain key infrastructure that facilitates the continuous development of these advanced capabilities. We regularly conduct on-robot testing and perform in-depth log analysis to continually enhance the performance and reliability of the solutions we offer our customers around the world.
In this role, you will:
Bring state-of-the-art AI methods out of the research lab and into the Stretch product
Help develop datasets, infrastructure, and tooling to build ML models at scale.
Advocate for and leverage the use of simulation tools (e.g. MuJoCo, Gazebo).
Integrate the use of novel techniques into Stretch software systems.
Collaborate with adjacent teams (e.g. Manipulation, Planning, SW Platform) to define requirements and propose solutions.
We are looking for:
MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
3 years of experience building robotic algorithms, including training and deploying AI policies, working with robot hardware, and leveraging simulation.
Strong foundation in Python and modern ML frameworks (e.g. PyTorch, Jax).
Strong analytical and debug skills.
Demonstrated ability to be successful in C++ and Python codebases.
Background in Reinforcement Learning, VLA models, or Behavior Cloning.
Nice to have:
Publications at top tier venues including RSS, CoRL, Science Robotics, ICLR, NeurIPS, CVPR is a plus.
Don't worry if your experience doesn't perfectly align with the qualifications. We are seeking candidates who are enthusiastic, eager to learn, and ready to grow with our team.
The base pay range for this position is between $154,000 to $222,000 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 an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.
