Machine Learning Engineer at Terranox AI

As the first dedicated ML hire, you will build the core systems that drive nuclear fuel discovery. You'll train custom computer vision models on complex, sparse geological data and deploy them into production. This is a high-impact role solving novel problems without an off-the-shelf playbook to address the global energy crisis.

• Design and train computer vision models from scratch using messy, sparsely-labeled geospatial and geological data sets.
• Build and maintain the end-to-end ML production pipeline that translates model outputs into real-world discovery decisions.
• Synthesize recent ML research into practical, shipped systems that address ambiguous problems in the nuclear energy sector.

• Has 5+ years of professional ML experience with a proven track record of taking complex systems from concept to production.
• Possesses deep expertise in computer vision and the ability to work comfortably with non-standard or sparse-label regimes.
• Thrives in early-stage environments, demonstrating the ability to frame and solve ambiguous problems independently in a fast-paced San Francisco office.

• Join as the first dedicated ML engineer at an early-stage company backed by premier investors including General Catalyst, 776 Ventures, and Y Combinator.
• Tackle a unique, high-stakes problem: using AI to solve the structural uranium shortage and enable scalable, clean baseload energy for the planet.
• Lead the development of a build-from-zero ML stack where you have full ownership over model architecture and production pipelines for multi-modal data.