As a VLA Research Scientist on the Atlas team, you will architect, train, and deploy the large-scale behavior models that enable high-performance dexterous manipulation on Atlas. Your work will focus on building models that take multimodal input (vision, language, tactile sensing, task context, robot state), and produce grounded actions that generalize across manipulation tasks, embodiments, and environments.
You will design large-scale behavior cloning and imitation learning pipelines, and integrate learned components into a complex, real-world robotic system. You’ll collaborate closely with robotics, controls, software, and hardware teams, and rapidly test your work on our state-of-the-art humanoid.
How You Will Make an Impact:
- Architect and train end-to-end VLA and Large Behavior Models for mobile manipulation on Atlas.
- Build large-scale imitation learning pipelines that learn from human demonstrations, teleoperation, and simulation data.
- Work on large pre-training across multiple data sources, and fine-tuning for precision tasks
- Develop policies capable of few-shot generalization across diverse factory manipulation tasks.
- Integrate your models into Atlas’s autonomy stack in collaboration with controls and platform teams.
- Deploy and iterate on our models with physical hardware and rigorous evals
- Write high-quality, maintainable Python code that fits into a large production codebase.
We’re Looking For:
- MS with 3+ years of experience or PhD in Machine Learning, Robotics, Computer Science, or related fields.
- Prior experience training and deploying learned policies for complex behaviors in robots or simulated characters.
- Strong background in:
- Behavior cloning / imitation learning
- Diffusion policies, World Actions Models, and other state-of-the-art methods
- Multimodal (vision/language/action/tactile) robot learning
- Experience with modern ML frameworks (PyTorch, JAX), simulators, and large-scale training workflows.
- Strong analytical and debugging skills; ability to write and review well-structured research code.
Nice to Have:
- Hands-on experience deploying learned policies on real robots.
- Experience creating or curating large robotics datasets (teleoperation, UMI, ego-centric video).
- Experience with RL as a complementary tool within behavior learning pipelines.
- Publications in top-tier ML or robotics conferences (e.g., CoRL, RSS, ICRA, NeurIPS).
- Experience contributing to large C++ or Python codebases.
Why Join Us:
- Direct access to an advanced humanoid robot—test your models on hardware quickly and often.
- A collaborative, inclusive team that values diverse perspectives and identities.
- The opportunity to do applied research with real-world impact.
- A mission-focused environment where your work will define the future of general-purpose humanoids.
The base pay range for this position is between $177,000 to $225,000 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.
