A stealth startup putting real-time AI guidance directly into the eyewear of field technicians maintaining critical infrastructure.
Founding ML Researcher
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We are training vision-language models that don't just see the world — they reason about it, overlay precise instructions onto a technician's field of view, and adapt when the unexpected happens inside a turbine housing or atop a transmission tower. As our first ML hire, you'll design the data flywheels, fine-tuning pipelines, and agent architectures that turn raw sensor streams into split-second, life-saving decisions. This means owning research from whiteboard to on-device deployment, collaborating directly with the two-person founding team in San Francisco, and shaping the scientific roadmap of a company that has the backing to pursue genuinely hard problems at the intersection of language, vision, and industrial reality.
What they're looking for
- Deep intuition for transformer architectures and multimodal training — you've built and debugged models in PyTorch, not just called APIs.
- Comfort stretching from research code to containerized services; experience with Docker and orchestration tools for reproducible experiments.
- Familiarity wiring language models into agentic workflows (e.g., LangChain or similar) and a strong opinion on where those abstractions break.
- 0–3 years of experience, which we interpret generously: open-source contributions, PhD work, hackathon projects, or industry internships all count.
- Genuine excitement about hardware constraints — you care about latency, memory budgets, and what it takes to run a model on a heatsink strapped to someone's temple.