Founding Research Engineer, Robot Learning
True Talent Solutions Partners · On site, San Francisco, US
260.000 - 300.000 USD / Jahr · Veröffentlicht am 5. Nov. 2026
Meine Bewerbung vorbereiten
Wir können Bewerbungen nicht für Sie an das Formular dieses Arbeitgebers senden. Wir bereiten Ihre Bewerbung aus Ihrem Lebenslauf vor, und Sie senden sie selbst ab.
Über die Stelle
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.
WHAT YOU'LL DO
- 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.
WHAT WE'RE LOOKING FOR
- 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.
COMPENSATION & BENEFITS
Base salary: $260,000 to $300,000 USD annually. Visa sponsorship is not available.
LOCATION
Hybrid role based in San Francisco, United States.
Ähnliche Stellen, auf die wir uns für Sie bewerben können
- Staff AI Agent Engineer | Moveworks
ServiceNow · Remote, US only · ML- und KI-Ingenieur
Veröffentlicht am 9. Nov. 2026
- Electrical Hardware Engineer, AI Satellites (Starmind)
SpaceX · Bastrop, US · ML- und KI-Ingenieur
Veröffentlicht am 9. Nov. 2026
- Optical Test Engineer, AI Satellites (Starmind)
SpaceX · Bastrop, US · ML- und KI-Ingenieur · 25 USD / Stunde
25 USD / Stunde
Veröffentlicht am 9. Nov. 2026
- Power Electronics Engineer, AI Satellites (Starmind)
SpaceX · Hybrid, Bastrop, US · ML- und KI-Ingenieur
Veröffentlicht am 9. Nov. 2026