Machine Learning Engineer (Robotics / Embodied AI)
San Francisco, United States
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou'll work at the intersection of robotics, computer vision, and foundation models—turning thousands of hours of human demonstrations into autonomous capabilities.
Design and implement data collection pipelines for synchronized sensor streams and task annotations from teleoperated robots.
Build data processing systems for cleaning, labeling, and organizing multi-modal data (RGB-D, LiDAR, proprioceptive feedback).
From the employer’s posting
Overview We're hiring a Machine Learning Engineer to lead our progression from teleoperation to autonomy. You'll use cutting-edge Vision-Language-Action (VLA) models and imitation learning to make our teleoperated robots increasingly autonomous over time. This role spans the full ML lifecycle: data capture and organization, model training and evaluation, deployment to edge devices, and continuous improvement based on real-world performance. You'll work at the intersection of robotics, computer vision, and foundation models—turning thousands of hours of human demonstrations into autonomous capabilities. What we do
What you'll do Design and implement data collection pipelines for synchronized sensor streams and task annotations from teleoperated robots. Build data processing systems for cleaning, labeling, and organizing multi-modal data (RGB-D, LiDAR, proprioceptive feedback).
Design and implement data collection pipelines for synchronized sensor streams and task annotations from teleoperated robots. Build data processing systems for cleaning, labeling, and organizing multi-modal data (RGB-D, LiDAR, proprioceptive feedback). Develop and train Vision-Language-Action models, imitation learning policies, and behavior cloning systems.
What you’ll bring
All qualificationsCore experience
- 3+ years of hands-on ML experience, preferably in robotics, computer vision, or embodied AI.
- Experience with imitation learning, behavior cloning, or reinforcement learning in physical systems.
- Proficiency with computer vision techniques (object detection, segmentation, point cloud processing).
- Understanding of robotics fundamentals (kinematics, control theory, sensor fusion).
- Strong Python skills and experience with ML libraries.
Qualification wording
3+ years of hands-on ML experience, preferably in robotics, computer vision, or embodied AI.
Experience with imitation learning, behavior cloning, or reinforcement learning in physical systems.
Proficiency with computer vision techniques (object detection, segmentation, point cloud processing).
Understanding of robotics fundamentals (kinematics, control theory, sensor fusion).
Strong Python skills and experience with ML libraries.
Tools in this posting
- Python
- PyTorch
- TensorFlow
Source — Tool mentions in context
- Understanding of robotics fundamentals (kinematics, control theory, sensor fusion). - Strong Python skills and experience with ML libraries. - Bonus: Experience with Vision-Language-Action models, foundation models, or deploying models to edge devices.
- 3+ years of hands-on ML experience, preferably in robotics, computer vision, or embodied AI. - Strong foundation in deep learning frameworks (PyTorch, JAX, TensorFlow) and training large models. - Experience with imitation learning, behavior cloning, or reinforcement learning in physical systems.
Job description
Overview
What we do
What you'll do
- Design and implement data collection pipelines for synchronized sensor streams and task annotations from teleoperated robots.
- Build data processing systems for cleaning, labeling, and organizing multi-modal data (RGB-D, LiDAR, proprioceptive feedback).
- Develop and train Vision-Language-Action models, imitation learning policies, and behavior cloning systems.
- Deploy trained models to edge compute devices with real-time inference constraints.
- Collaborate with Robotics and Teleop teams to define autonomous capabilities and integrate models into the control stack.
What you bring
- 3+ years of hands-on ML experience, preferably in robotics, computer vision, or embodied AI.
- Strong foundation in deep learning frameworks (PyTorch, JAX, TensorFlow) and training large models.
- Experience with imitation learning, behavior cloning, or reinforcement learning in physical systems.
- Proficiency with computer vision techniques (object detection, segmentation, point cloud processing).
- Understanding of robotics fundamentals (kinematics, control theory, sensor fusion).
- Strong Python skills and experience with ML libraries.
- Bonus: Experience with Vision-Language-Action models, foundation models, or deploying models to edge devices.
Additional Notes
- Our team develops on physical robots in person—expect hands-on testing and debugging
- Need to be located or willing to relocate to San Francisco, CA
- Opportunity to shape the autonomy roadmap for a rapidly scaling robot fleet
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on avatarrobotics.zohorecruit.com. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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- Status in our records
- Active
- First seen by us
- Jun 3, 2026
- Recorded sightings
- 46
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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