Research Scientist

About Verne

Verne Robotics builds robotic arms and learning systems for real-world manipulation tasks. Our work connects robot hardware, data collection, policy learning, and deployment.

The Role

We’re looking for a Research Scientist to develop learning methods that help robots acquire useful manipulation skills and perform them reliably. You’ll work across data, models, and physical experiments, turning research ideas into policies that can be evaluated on real robots.

What You’ll Do

• Develop and evaluate methods for robot manipulation, including imitation learning, reinforcement learning, and vision-based policies.

• Design experiments to improve task success, generalization, robustness, and data efficiency.

• Train models on robot demonstrations and multimodal sensor data; investigate failures and identify the data needed to improve performance.

• Build reproducible training and evaluation workflows with clear baselines, metrics, and experiment records.

• Test policies on physical robots and collaborate with engineering on inference, control integration, and deployment.

• Communicate results clearly and use experimental evidence to guide the next iteration.

What You Bring

• Research experience in robot learning, machine learning, computer vision, or a closely related field.

• Strong Python and PyTorch skills, with experience implementing, training, and debugging learning systems.

• A track record of rigorous experiments and meaningful results, demonstrated through research papers, projects, open-source work, or deployed systems.

• Experience with robotic systems or a strong interest in hands-on experimentation with physical hardware.

• The ability to work independently, collaborate closely, and explain technical tradeoffs clearly.

• A Ph.D. in a relevant field or equivalent research experience.

Useful Additional Experience

• Visuomotor policies, diffusion policies, or vision-language-action models.

• Manipulation, teleoperation, reinforcement learning, or sim-to-real transfer.

• Large-scale training, multimodal datasets, and systematic policy evaluation.

Location and Compensation

• Full-time, on-site in South San Francisco, California.

• Annual base salary: $200,000–$350,000 USD.

Apply

Tell us about research or systems you’ve built, what you learned from the results, and why you want to work on robots in the real world. Links to papers, code, project write-ups, or demonstrations are welcome.

Compensation

$200K – $350K