Machine Learning Engineer (Robotics / Embodied AI)

Avatar Robotics

$135K — $160K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of hands-on ML experience in robotics, computer vision, or AI.
  • Proficient in deep learning frameworks like PyTorch, JAX, or TensorFlow.
  • Experience with imitation learning, behavior cloning, or reinforcement learning in physical systems.
  • Strong grasp of computer vision techniques such as object detection and segmentation.
  • Fundamental understanding of kinematics, control theory, and sensor fusion in robotics.
  • Proficiency in Python and ML libraries for effective coding and model training.
  • Bonus: Familiarity with Vision-Language-Action models and edge device deployment.

Responsibilities

  • Design and implement data collection pipelines for teleoperated robots.
  • Build systems for cleaning, labeling, and organizing multi-modal data streams.
  • Develop and train Vision-Language-Action models and imitation learning policies.
  • Deploy trained models on edge compute devices ensuring real-time inference.
  • Collaborate with Robotics and Teleop teams to enhance autonomous capabilities.

Benefits

  • Opportunity to shape the autonomy roadmap for a scaling robot fleet.
  • Hands-on testing and debugging experience with physical robots.
  • Work in vibrant San Francisco, CA, or willingness to relocate.
Full Job Description
Job Description
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 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

Come join us in building a new global economy, where anyone can do manual work remotely and with robo-scale. Together, we can make goods and resources more affordable and available than they've ever been, for everyone on Earth.

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