Description
We are seeking a Senior Manipulation Engineer to develop learned manipulation policies for robotic platforms operating in unstructured environments. You will build the skill policies that enable our systems to grasp objects, operate tools, turn valves, open doors, and perform assembly tasks , trained from human demonstration data and deployed on real hardware. You will own the full loop: teleoperation data collection, policy training, real-world evaluation, and iteration.
Key responsibilities include:
- Design, train, evaluate, and deploy visuomotor manipulation policies using behaviour cloning and imitation learning (ACT, Diffusion Policy, VLA models)
- Build and maintain the teleoperation and data collection pipeline for real-robot demonstration capture
- Develop task-specific skill policies for grasping, tool use, bimanual manipulation, and assembly operations
- Own the full pipeline from data collection to model training, evaluation, and deployment on embedded compute
- Collaborate with locomotion engineers to integrate manipulation skills into a whole-body control architecture
- Work with perception engineers to design vision inputs for skill policies
Required qualifications include:
- 3+ years of experience developing and deploying robot learning systems on real robots
- Strong background in robot manipulation and visuomotor control
- Experience with behaviour cloning, imitation learning, or related methods
- Hands-on experience with teleoperation systems and demonstration data collection
- Proficiency in Python, PyTorch, and modern deep learning frameworks
- Experience with LeRobot, ACT, Diffusion Policy, or similar IL frameworks
- Eligible to obtain and maintain a U.S. security clearance
Preferred qualifications include:
- Experience deploying learned manipulation in production or commercial robotic systems
- Experience with dexterous hands or multi-fingered grippers
- Prior work on bimanual manipulation
- Publications in manipulation, robot learning, or embodied AI
This listing is enriched and indexed by YubHub. To apply, use the employer's original posting:
https://job-boards.greenhouse.io/andurilindustries/jobs/5136832007