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About the role
This role sits between ML engineering and research. You’ll bring strong ML engineering skills, a research mindset, and deep learning fundamentals to the hardest problems we see coming at Trace, then ship the answers into production. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A BS in Computer Science, Electrical Engineering, Mathematics, Aerospace, or a related field, or equivalent practical experience. An MS is a plus, not a must
- 2+ years of industry of hands-on experience training deep learning models on real-world data, at a company, startup, or national lab. Earlier in your career is okay if your track record shows it
- Strong proficiency in Python and a modern deep learning framework such as PyTorch or JAX
- A solid grounding in ML fundamentals, including architectures, optimization, loss design, and evaluation
- Comfort with messy, real-world data such as video, time series, or sensor streams
- An extraordinary bias toward shipping. You go from idea to working model fast, and you make good calls under uncertainty
More about this role
Trace Labs is building the data infrastructure 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 held back by one big gap: there’s no scalable way to collect high-quality, real-world training data. Frontier robotics models are trained on far less data than language models, because there’s no “internet of robotics data.”
Trace exists to change that. We capture how humans actually interact with the physical world, at scale, and we build the ML systems that make every hour of that data more valuable.
We’re an early, deeply technical team. We move fast, we care about quality, and we believe the teams with the best data will build the best robots.
This role sits between ML engineering and research. You’ll bring strong ML engineering skills, a research mindset, and deep learning fundamentals to the hardest problems we see coming at Trace, then ship the answers into production.
You’ll work closely with our computer vision team, but this role is broader and more product-focused. You won’t live on one type of data. One month you...
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