Trace is building the data marketplace for physical AI.
Physical AI has the potential to transform how work gets done in the real world, from robotics to embodied systems that can see, move, and interact with their environment. But today, progress is constrained by a fundamental limitation: there is no scalable way to collect high-quality, real-world training data. Frontier robotics models are trained on orders of magnitude less data than language models because there is no equivalent of an “internet of robotics data.”
Trace exists to change that.
We build the infrastructure that makes it possible to capture and transform real-world data from humans performing physical work, and turn it into training data for robotics systems, embodied AI models, and other AI systems that operate outside the browser and in the physical world.
If we succeed, we meaningfully accelerate the development of physical AI and expand what these systems can safely and reliably do in the world. Our platform is designed to support many data formats, capture workflows, and customer needs over time. What we capture today is only the starting point.
If you want to be an early hire at a company helping define how robots learn to work, keep reading.
A world-changing problem: Physical AI will reshape entire industries, but it cannot scale without real-world data. Trace is addressing one of the core constraints holding the field back.
Early but real traction: Active pilots with growing demand on both sides of the marketplace.
Experienced, tight-knit team: Ex founders, PhDs, and operators with a track record of building and scaling together.
Real ownership: This is early. Your work will materially shape the product, systems, and direction of the company.
Foundational platform: We are building core infrastructure that enables many future products and use cases as physical AI evolves.
This is a backend-heavy role focused on the systems that move and transform data from capture to usable datasets. You will own reliability and throughput across the pipeline and build the infrastructure that makes real-world data collection viable at scale.
Build and scale our capture-to-cloud pipeline (ingestion, uploads, processing, storage, access)
Drive performance work across compression, reliability, observability, and robustness of our data pipeline.
Build internal services and tools that unblock capture and operations teams
Partner closely with ops to shorten the loop from capture to customer-ready data
Help define technical direction and engineering best practices as the team scales
Strong backend fundamentals: distributed systems, APIs, databases, queues, storage
Experience owning systems end to end, including when things break
Comfort operating without a lot of structure and helping create it
Product-minded builder who is comfortable translating real world feedback into better systems and experiences
Clear communicator with high accountability
Emotional maturity and good judgment under pressure
Robotics, autonomy, CV, or sensor-adjacent environments
Video pipelines, media processing, or large-file transfer experience
Internal tooling or ops-support systems