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Clera

Research Engineer / Research Scientist, Robotics and Physical AI

San Francisco$100k–$300kfulltimemidAdded today

About this role

Join an early-stage AI company developing high-quality training data for robotics and frontier models. You'll work across the full stack—from learning algorithms and simulation to real hardware—bridging synthetic environments with reliable real-world robot deployment.

What you'll do

  • Develop learning systems including policies, world models, and vision-language-action models for robots
  • Build and maintain simulation environments and evaluation frameworks for robotic tasks
  • Apply computer vision and perception algorithms for autonomous robot systems
  • Create sim-to-real and real-to-sim pipelines connecting simulation to physical robot deployment
  • Work with robot hardware, sensors, actuators, and embedded systems for prototyping and testing
  • Train and evaluate reinforcement-learning and imitation-learning systems for manipulation and locomotion

What they're looking for

  • C++ and Python programming
  • Deep learning and reinforcement learning
  • Computer vision
  • Robotics simulation (Isaac Lab, MuJoCo, MJX, Genesis)
  • Robot hardware and embedded systems
  • CAD or 3D modeling (Blender)
  • Imitation learning
  • Transformers and multimodal AI (plus)

Benefits

  • Equity participation at early stage
  • Hands-on work across full robotics stack
  • Collaboration with external robotics companies and research labs
  • On-site presence in San Francisco tech hub
  • Work on frontier AI and robotics problems
  • Experience spanning research and product development
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

View all jobs at Clera

Likely interview questions

  • Describe a project where you bridged simulation and real-world robotics—what were the key sim-to-real challenges you faced?
  • Walk us through your experience training RL or imitation-learning systems; which framework did you use and why?
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