Startups · AI

Machine Learning / Computer Vision Engineer

Eka Robotics · Boston Area · On-site

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About Eka Robotics

The Era of Superhuman Robotics. Backed by a16z.

About the role

Build computer vision and visual representation learning pipelines for robotic manipulation, including RGB, RGB-D, depth, segmentation, pose, keypoint, and object-centric representations. Develop visual models that support reinforcement learning and imitation learning policies, including end-to-end visuomotor policies that map visual observations to robot actions.

What they're looking for

  • Ph.D. in computer vision or 3+ years of experience working on a computer vision product
  • Strong background in machine learning for computer vision, especially deep learning-based visual perception
  • Experience training modern computer vision models in Jax, PyTorch or similar frameworks
  • Practical experience with visual representation learning, object detection, segmentation, pose estimation, depth estimation, tracking, or 3D perception
  • Strong Python programming skills
  • Ability to move fluidly between research code and production-quality systems
More about this role

Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable. Our approach, grounded in physics, unlocks superhuman capabilities. We are defining the frontier of robotics research and deployment.

Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D effort. We are looking for hands-on individuals who are excited to help shape the future of robotics.

Build computer vision and visual representation learning pipelines for robotic manipulation, including RGB, RGB-D, depth, segmentation, pose, keypoint, and object-centric representations.

Develop visual models that support reinforcement learning and imitation learning policies, including end-to-end visuomotor policies that map visual observations to robot actions.

Improve our data pipeline for vision-based manipulation policies through domain randomization, photorealistic rendering, synthetic data generation, sensor noise modeling, and real-world fine-tuning.

Design and train perception models that are robust to lighting changes, camera viewpoint shifts, texture variation, clutter, occlusion, object instance variation, and imperfect...

Read the full posting on Eka Robotics's site ↗

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