Hiring Research Scientists and Research Engineers at PerfectBit

Research Engineers & Research Scientists — Physical AI Data
San Francisco · on-site

About the team

• Peter Vajda — former Director of Media Generation at Meta Superintelligence Labs, where he led the foundation models behind Movie Gen and Emu; previously a Visiting Assistant Professor at Stanford. PhD in computer science.
• Seiji Yamamoto — former Senior Staff Research Scientist at Meta Superintelligence Labs, where he led teams in the Core Llama group across LLM pre- and post-training, inference, speech, and vision. PhD in physics.

About the company

• PerfectBit is a new kind of data company, built to solve the biggest bottleneck in physical AI: data. The real-world interaction data that robots and world models need doesn't exist on the internet — it has to be created. Most data companies attack this by scaling networks of human experts. We don't. We use applied AI to build novel solutions to the data problems slowing down robotics, world models, and physical AI. Our quality and scale come from better methods, not just more headcount.

Who we’re seeking

• High agency and autonomy — you find the work, scope it, and ship it.
• You've built and shipped real systems (data, ML, infra), not just prototypes and toy projects.
• You care about outcomes and the mission, not performance reviews.
• You thrive working closely with a small, collaborative team.
• You get serious leverage out of AI coding tools (Claude, Codex) and use them to move fast.
• Strong candidates may also have a track record of research at leading venues (NeurIPS, ICLR, CVPR, ICCV, ICRA, CoRL) and/or depth in one or more of: reinforcement learning; robotics; multimodal models (LLMs, VLMs, VLAs, world models, WAMs, diffusion and flow-matching); synthetic data generation; simulation (Isaac, MuJoCo/MJX, Genesis); 3D/graphics (Blender, CAD, Gaussian splatting/NeRF); teleop and data-collection hardware; evals; AI infra; pre-/post-training; AI Agents

Location

• On-site in San Francisco (this role is not remote)

Compensation

•  $150K–$300K base + meaningful equity