Platform that vets hardtech talent through immersive real-world simulations
Founding Machine Learning Engineer
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You'll spend mornings sketching out new model architectures for evaluating robotics and hardware candidates, and afternoons shipping PyTorch pipelines that power full-day simulation assessments. This means building retrieval systems on vector databases, refining how multimodal inputs translate to hiring signals, and occasionally walking factory floors to understand what separates a promising engineer from a proven one. As the first ML hire, you will define the research culture—deciding which experiments deserve compute, which metrics actually predict on-the-job performance, and when to trade theoretical elegance for production robustness.
What they're looking for
- 3+ years shipping production ML systems, preferably with computer vision or multimodal applications
- Deep fluency in PyTorch and Python; you've debugged distributed training runs at 3 AM
- Hands-on experience with vector databases and embedding-based retrieval architectures
- Comfort translating between messy physical-world data and clean model inputs—hardware, robotics, or defense exposure helps
- Willingness to work hybrid in San Francisco and occasionally visit manufacturing or testing sites