Job Description
Our AI Research team is building end-to-end robot policies that enable dexterous manipulation in real-world environments. We are advancing embodied AI by integrating multimodal perception robot learning architectures and physical execution systems to solve manipulation autonomy and simulation challenges at industrial scale.
As a Staff Applied Scientist you will lead the development of core components of these embodied systemsfrom model design and training pipelines to integration with perception motion control and hardware. You will design prototype and deploy robot learning models that span perception policy learning simulation and real-world execution collaborating closely with robotics engineers AI infrastructure teams and production experts.
What Youll Do
Design and implement advanced robot learning architectures (e.g. diffusion policies ACT VLM/VLA-guided agents imitation learning) to support dexterous manipulation path planning and autonomous task sequencing.
Develop end-to-end policy training pipelines integrating multi-modal sensory data (RGB depth proprioception force/torque LiDAR tactile inputs) with control outputs.
Build policy inference and closed-loop control that connect perception planning and execution on physical robotic platforms.
Apply and extend large-scale architecturesLLMs VLM/VLAs diffusion modelsto embodied tasks grounding and sim-to-real adaptation.
Collaborate with cross-functional teams to deploy robot policies on hardware ensuring robustness repeatability and safety.
Lead data strategy for demonstrations teleoperation simulation pipelines and evaluation frameworks for manipulation policies.
Stay current with embodied AI research and share insights internally through discussion mentorship and technical presentations.
Required Qualifications
PhD in a relevant STEM field or Masters with equivalent industry experience in robotics robot learning or embodied AI.
Proven experience building and deploying machine learning models on robotic systemsincluding training evaluation and real-world execution or simulation.
Deep understanding of modern AI architectures (e.g. Transformers diffusion models VLM/VLAs CNNs) with strong experience training models at scale.
Strong PyTorch implementation skills including authoring custom modules batching debugging and performance optimization.
Practical experience with ROS/ROS2 and integrating learned policies into manipulation or motion control workflows.
Demonstrated impact via robot learning publications open-source contributions or production robotics deployments.
Preferred Qualifications
Experience developing robot learning systems for dexterous manipulation multi-step task execution or autonomous behaviors.
Expertise in robotics perception including 3D understanding force sensing tactile feedback multimodal fusion or affordance modeling.
Familiarity with Isaac Sim Mujoco Gazebo PyBullet or custom simulators and demonstrated ability to transfer policies to hardware.
Experience adapting foundation models (VLM/VLAs diffusion instruction-following agents) for embodied control tasks.
Track record of production-ready robotics systems reproducible research artifacts or deployments in physical environments.
Why Join Us
You will help build robotic agents that can manipulate the world with dexterity and autonomy. Your work will directly influence how robots perceive act and adapt across GMs global ecosystem.
Location: This role is categorized as hybrid. This means the successful candidate is expected to report to the MTV office three times per week or any other frequency dictated by the business.
Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York Colorado California or Washington.
Company Vehicle: Upon successful completion of a motor vehicle report review you will be eligible to participate in a company vehicle evaluation program through which you will be assigned a General Motors vehicle to drive and evaluate.
Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
Relocation: This job may be eligible for relocation benefits.
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