Staff Research Engineer

I'm partnering with a ~$9B frontier AI company building next-generation embodied AI and world models.

They're looking for an exceptional Principal/Staff+ Research Engineer to tackle one of the hardest problems in frontier AI:

Given massive amounts of multimodal data and compute, how do you determine which data will actually make the next model better - before you train it?

You'll work across:

• Dataset enrichment and evaluation
• Understanding how training data impacts downstream model performance
• World models / frontier multimodal AI
• Technical strategy across research, data & model teams

This is a highly senior IC role with significant technical influence across the organization, not simply a data pipeline or infrastructure position.

Ideal background:

• Experience working with multimodal, image, video, robotics or other large-scale ML datasets
• Deep understanding of data quality and its relationship to model performance
• Experience operating at genuine frontier-model / production scale
• Strong cross-functional technical leadership and judgment
• Comfortable solving ambiguous, open-ended research and engineering problems

Autonomous driving experience is NOT required. We're particularly interested in people from frontier AI labs, multimodal/video foundation-model teams, robotics, and other organizations solving data problems at enormous scale.

Bay Area / London + flexibility for exceptional candidates

If you've worked on understanding what makes data valuable for training frontier models, I'd love to hear from you.