AI Research Engineer

Cerebro; San Francisco (CA); On-site; USD 160,000 - 210,000; Full time

Job summary

Cerebro in San Francisco is seeking researchers and engineers to join an early-stage, on-site team building embodied AI for robotics. This is a founding team role where you’ll influence technical direction, identify core research problems, and translate ambitious ideas into working systems.

Candidates should be comfortable moving between research, engineering, and real-world experimentation, and have a track record of delivering substantial systems across robotics, ML, simulation, hardware, or

Qualifications

• Experience across robotics, machine learning, simulation, hardware or research infrastructure.
• Ability to work autonomously in ambiguous problems.
• Strong track record delivering substantial systems in complex domains.

Responsibilities

• Shape the technical direction of Cerebro and define key research problems.
• Turn ambitious ideas into functioning robotics/AI systems that improve performance in the physical world.

Job description

Founding Robotics & Embodied AI Engineers / Researchers

San Francisco — on-site

I’m partnering with an early-stage Physical AI company founded by two former senior research leaders from Meta Superintelligence Labs.

Between them, the founders have led teams working across multimodal foundation models, LLM pre-training and post-training, inference, speech, vision and media generation. They are now building AI systems that help robots learn, reason and operate effectively in the physical world.

The team is making several foundational hires across robotics research and engineering. Depending on your background, you could work on:

• Reinforcement learning and imitation learning for manipulation, locomotion, humanoids or mobile robots
• Vision-language-action models, world models and robot policies
• Simulation environments using Isaac Lab, MuJoCo, MJX, Genesis or similar platforms
• Real-to-sim, sim-to-real and real-to-sim-to-real pipelines
• Computer vision and perception for autonomous robotic systems
• Robot hardware, sensors, actuators and embedded systems
• Evaluation frameworks and benchmarks for embodied models
• Research infrastructure connecting simulation with real-world deployment

This isn’t a narrowly defined implementation role. You’ll help shape the technical direction of the company, identify important research problems and turn ambitious ideas into systems that demonstrably improve robot performance.

You could be a strong fit if you’ve built substantial systems across robotics, machine learning, simulation, hardware or research infrastructure—and are comfortable moving between research, engineering and real-world experimentation.

The team is particularly interested in people who:

• Operate with significant autonomy
• Thrive when problems are ambiguous
• Care about measurable technical progress
• Can move quickly from an idea to a working system
• Want to develop new methods rather than follow an established playbook
• Enjoy working directly with robots, simulators and hardware

This is an opportunity to join an unusually experienced founding team at the earliest stage and play a meaningful role in building the intelligence layer for physical AI.

The position is fully on-site in San Francisco and cannot be performed remotely.