Clera Research Engineer / Scientist role at Clera developing AI systems for robotics to enable real-world deployment. Works across learning algorithms, simulation, and hardware integration.
Responsibilities
This role sits at the intersection of research and engineering on a small, high-output team building AI systems that help robots learn, reason, and operate in the physical world. You'll work across learning algorithms, simulation, and hardware to push robot capabilities from simulation into real-world deployment — directly shaping how robots perceive, plan, and act.
Develop learning systems for robots, including policies, world models, and vision-language-action models.
Build and maintain simulation environments and evaluation frameworks for robotic tasks.
Apply and advance computer vision and perception algorithms for autonomous robots.
Build pipelines connecting simulation and real-world robot deployment (sim-to-real and real-to-sim).
Work with robot hardware, sensors, actuators, and embedded systems to prototype and test capabilities.
Train and evaluate reinforcement-learning and imitation-learning systems for manipulation, locomotion, or mobile platforms.
Integrate and experiment with robot platforms to validate algorithms in the physical world.
Create tools and infrastructure that accelerate robotics research and development.
Collaborate with external robotics companies and research labs on technical problems.
Qualification
Practical experience with deep learningExperience with robotics hardwareComfort moving fluidly between researchExposure to modern ML tools — LLMs
Required
Any experience level welcome — new graduates through senior researchers and engineers are encouraged to apply.
Strong software skills in C++ and Python.
Practical experience with deep learning, reinforcement learning, and computer vision.
Hands-on experience with robotics simulation platforms such as Isaac Lab, MuJoCo, MJX, or Genesis, and with real-to-sim/sim-to-real workflows.
Experience with robotics hardware, sensors, actuators, CAD/Blender, and embedded systems.
Comfort moving fluidly between research, engineering, experimentation, and product development in a small team.
Exposure to modern ML tools — LLMs, Transformers, multimodal AI, diffusion models, or AI agents — is a plus.
Preferred
Exposure to modern ML tools such as LLMs, Transformers, multimodal AI, diffusion models, or AI agents
