Founding Research Engineer

Description

About the Role

As the first robot learning hire, you will bring policy training and evaluation in-house at a physical AI data and simulation company. Working with research, engineering, and product teams, you will establish whether synthetic training data improves robot performance and turn findings into product requirements.

Responsibilities

• Train robot policies using synthetic data, including VLA fine-tuning, imitation learning, diffusion policies, or reinforcement learning in simulation.
• Establish baselines on public evaluation suites and run controlled comparisons to measure the impact of training data on manipulation and grasping.
• Document results honestly, including unsuccessful experiments, and use evaluation findings to guide subsequent data and simulation changes.
• Translate experimental findings into written specifications for data generation, fidelity, and variation.
• Publish and demonstrate results to the robotics community and participate in customer technical discussions.
• Help build and lead the robotics team as it grows.

Requirements

• At least 6 years of hands-on robot learning experience, including work in industry and a university research lab.
• A master's or doctoral degree in robotics, machine learning, or a related field.
• Experience training and evaluating robot policies in simulation with Isaac Sim, Isaac Lab, MuJoCo, or equivalent tools.
• Practical experience with policy learning methods such as VLA fine-tuning, imitation learning, diffusion policies, ACT, behavior cloning, or reinforcement learning.
• Experience with manipulation or grasping policies; navigation policy experience is also relevant.
• Ability to run controlled experiments with fixed seeds, checkpoints, and evaluation suites, changing only the training data.
• Experience using evaluation results to guide data or simulation changes for subsequent training iterations.
• Relevant tools include Python, PyTorch, NVIDIA Isaac, and USD.

Conditions

Base salary: $260,000 to $300,000 USD annually. Visa sponsorship is not available.

Hybrid role based in San Francisco, United States.