3 часа назад
Research Scientist, VLA Models - Atlas (AI)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Research Scientist, VLA Models - Atlas (AI): Architecting, training, and deploying large-scale vision-language-action and behavior models for dexterous mobile manipulation on the Atlas humanoid robot with an accent on imitation learning, multimodal modeling, and hierarchical skill systems. Focus on building few-shot generalization, integrating learned policies into the autonomy stack, and debugging models directly on physical hardware.
Location: Waltham Office, United States
Company
develops advanced humanoid robotics, including the Atlas platform.
What you will do
- Architect, train, and deploy end-to-end vision-language-action and large behavior models for mobile manipulation on Atlas.
- Build imitation learning pipelines using human demonstrations, teleoperation, and simulation data.
- Develop policies with few-shot generalization across diverse manipulation tasks, embodiments, and environments.
- Create hierarchical behavior systems that combine learned skills into long-horizon behaviors.
- Integrate learned models into Atlas’s autonomy stack with robotics, controls, and platform teams.
- Deploy, debug, and iterate models on physical humanoid hardware while writing maintainable Python and C++ code.
Requirements
- MS with 3+ years of experience or PhD in Machine Learning, Robotics, Computer Science, or a related field.
- Experience training and deploying learned policies for complex behaviors in robots or simulated characters.
- Strong background in behavior cloning, imitation learning, diffusion policies, ACT, large behavior models, sequence modeling, and multimodal vision-language-action learning.
- Experience with PyTorch, JAX, and large-scale machine learning training workflows.
- Strong analytical and debugging skills, with the ability to write reliable, well-structured research code.
Nice to have
- Hands-on experience deploying learned policies on real robots.
- Experience creating or curating large demonstration datasets from teleoperation, human demonstrations, or egocentric video.
- Experience using reinforcement learning as a complementary tool in behavior learning pipelines.
- Publications in top-tier machine learning or robotics conferences such as CoRL, RSS, ICRA, or NeurIPS.
- Experience contributing to large C++ or Python codebases.
Culture & Benefits
- Direct access to an advanced humanoid robot for frequent hardware testing.
- Collaborative and inclusive working environment that values diverse perspectives and identities.
- Opportunity to conduct applied vision-language-action research with real-world impact.
- Mission-focused work on general-purpose humanoid robotics.
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