Research Engineer

Cerebro; San Francisco (CA); On-site; USD 200,000 - 300,000; Full time

Job summary

Cerebro Partners is partnering with an early-stage, YC-backed robotics company developing learned manipulation and control policies for real-world environments. We’re seeking a Robotics Research Engineer to own difficult problems across learning, simulation and physical deployment, joining one of the earliest research teams.

You’ll work closely with founders, shaping technical direction as the team forms. Open to candidates who can bridge research and implementation while delivering measurable

Qualifications

• You’ve built substantial systems in robotics, machine learning, simulation, hardware or research infrastructure.
• You’re comfortable taking an ambiguous problem and finding a practical place to start.

Responsibilities

• Develop reinforcement and imitation learning systems for manipulation, humanoids, locomotion and mobile robots.
• Build simulation environments with platforms such as Isaac Lab, MuJoCo, MJX or Genesis.
• Train and evaluate robot policies, world models and vision-language action models.
• Connect simulation with physical experiments through sim-to-real and real-to-sim workflows.
• Integrate hardware, sensors and actuators to test new capabilities.
• Design evaluations that make progress measurable and expose where systems break.

Job description

Build the systems that turn advances in AI into capable robots.

How do you teach a robot to operate when its environment changes, the task is unfamiliar and the next action has physical consequences?

That question sits at the centre of the company we’re helping build.

Cerebro Partners is partnering with an early stage, YC backed robotics company developing learned manipulation and control policies for real world environments. We’re looking for a Robotics Research Engineer who wants to own difficult problems across learning, simulation and physical deployment.

The team behind it

The founders bring substantial research leadership experience from Meta, spanning generative image and video models, language model training, inference and computer vision. Their backgrounds combine foundation model development with deep scientific training in computer science and physics.

Now they’re building a small team around a new challenge: translating that experience into robotic capabilities that hold up outside the lab.

You’ll join among the earliest researchers and engineers, working directly with the founders while the technical direction is still taking shape.

What you’ll build

Your focus will reflect your strongest skills. Potential areas include:

• Developing reinforcement and imitation learning systems for manipulation, humanoids, locomotion and mobile robots.
• Building simulation environments with platforms such as Isaac Lab, MuJoCo, MJX or Genesis.
• Training and evaluating robot policies, world models and vision language action models.
• Connecting simulation with physical experiments through sim to real and real to sim workflows.
• Integrating hardware, sensors and actuators to test new capabilities.
• Designing evaluations that make progress measurable and expose where systems break.

The appeal is the full experimental loop: formulate an idea, build the system, test it and use what happens to decide what comes next.

Who we’d like to meet

You’ve built substantial systems in robotics, machine learning, simulation, hardware or research infrastructure. You’re comfortable taking an ambiguous problem and finding a practical place to start.

You should enjoy moving between research and implementation, taking responsibility for experiments and collaborating closely with a small technical team.

Bring evidence of your work. A research project, a deployed system, an open source contribution or a robot you’ve spent months getting to behave can give us something meaningful to discuss.

There is a particular kind of satisfaction in joining early enough that your engineering decisions become part of how a company works.

Here, you’ll have scope to influence the research agenda, build foundational systems and help determine which ideas deserve further investment. For someone who wants both technical depth and ownership, that is the opportunity.

$200,000–$300,000 base salary, plus equity. Based onsite in San Francisco.