Research Scientist, VLA Models - Atlas
- 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.
- Develop policies capable of few-shot generalization across diverse manipulation tasks.
- Create hierarchical behavior systems that combine learned skills into long-horizon behaviors.
- Integrate your models into Atlas’s autonomy stack in collaboration with controls and platform teams.
- Deploy, debug, and iterate your models directly on physical hardware.
- Write high-quality, maintainable Python and C++ code that fits into a large production codebase.
- 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, ACT, or other modern BC architectures
- Large behavior models or sequence modeling
- Multimodal (vision/language/action) learning
- Experience with modern ML frameworks (PyTorch, JAX) and large-scale training workflows.
- Strong analytical and debugging skills; ability to write reliable, well-structured research code.
- Hands-on experience deploying learned policies on real robots.
- Experience creating or curating large demonstration datasets (teleop, human demos, 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.
- 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 VLA research with real-world impact.
- A mission-focused environment where your work will define the future of general-purpose humanoids.
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