Clera
Research Engineer / Research Scientist — Robotics & Physical AI
About this role
Join a Y Combinator-backed Physical AI startup to develop learning systems, simulation environments, and perception algorithms that enable robots to learn and operate in the real world. This hands-on role bridges research and engineering, combining algorithm development with hardware experimentation and infrastructure building.
What you'll do
- Develop robot learning systems including policies, world models, and vision-language-action models
- Build and maintain simulation environments and evaluation frameworks for robotic tasks
- Apply computer vision and perception algorithms for autonomous robot perception
- Design sim-to-real and real-to-sim pipelines for robot deployment
- Train and evaluate reinforcement-learning and imitation-learning systems for manipulation and locomotion
- Work with robot hardware, sensors, and embedded systems to prototype and validate algorithms
What they're looking for
- Robotics simulation (Isaac Lab, MuJoCo, MJX, Genesis)
- Reinforcement learning and imitation learning
- C++ and Python
- Computer vision and deep learning
- Robot hardware and embedded systems
- Sim-to-real transfer and domain adaptation
- Machine learning infrastructure and tools
- CAD or 3D modeling (Blender)
Benefits
- Competitive salary up to $300,000 USD annually
- Equity participation in venture-backed startup
- Work on cutting-edge robotics and Physical AI research
- Cross-functional collaboration on real-world robot deployment
- Access to robot hardware and simulation infrastructure
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
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 CleraLikely interview questions
- Walk us through a robotics simulation project you built—what framework did you use and what challenges did you encounter in sim-to-real transfer?
- Describe your experience training RL or imitation-learning systems for robot control. How did you handle exploration, data collection, and evaluation?