Machine Learning Engineer at Terranox AI

Jack & Jill; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Terranox AI in San Francisco is hiring the first dedicated ML engineer to build core machine learning systems from scratch, developing computer vision models with sparse, messy data to support uranium discovery. You’ll take models from research to production in a field critical to global energy security.

This hands-on role offers ownership of architecture and production pipelines, and the chance to translate the latest ML research into practical, shipped systems that drive real-world decisions

Qualifications

• At least 5 years of professional ML experience.
• Strong background in computer vision and production environments.
• Ability to translate research into shipped systems in an early-stage startup.

Responsibilities

• Design and train custom computer vision models from scratch on messy and sparsely-labeled datasets.
• Architect and deploy end-to-end ML production pipelines that integrate into real-world exploration workflows.
• Translate the latest machine learning research into practical, shipped systems that disrupt traditional discovery processes.

Skills

Machine Learning

Computer Vision

Production Pipelines

Research Translation

Job description

This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers. She will pick the best candidates from Jack’s network.

The next step is to speak to Jack.

Job Title

Machine Learning Engineer

Salary

Not Disclosed

Company Description

Terranox AI is a venture-backed startup supported by General Catalyst, 776 Ventures, and Y Combinator, applying machine learning to modernize the uranium discovery process to secure the future of clean, scalable nuclear energy.

Job Description

As the first dedicated ML hire at Terranox AI, you will build core machine learning systems from scratch. You’ll develop computer vision models using sparse, messy data to drive real-world discovery decisions. This hands‑on role involves taking models from research to production in a field critical to global energy security.

Location

San Francisco, USA

Why this role is remarkable

• Join as the first ML hire, giving you complete ownership over the technical architecture and strategy for the world’s first AI-powered uranium discovery company.
• Work on a mission-critical problem: solving the structural shortage of uranium to enable clean, scalable, baseload nuclear energy globally.
• Benefit from high-tier backing by investors like General Catalyst, 776 Ventures, and Y Combinator while working in an early-stage, build-from-zero environment.

What You Will Do

• Design and train custom computer vision models from scratch, specifically handling messy and sparsely-labeled datasets unique to geological discovery.
• Architect and deploy end-to-end ML production pipelines that integrate directly into real-world decision-making and exploration workflows.
• Translate the latest machine learning research into practical, shipped systems that disrupt a discovery process that hasn’t changed in decades.

The ideal candidate

• Has at least 5 years of professional ML experience with a proven track record of building complex systems from the ground up.
• Possesses a strong background in computer vision and experience taking machine learning models all the way through to production environments.
• Demonstrates fluency with recent ML research and the ability to frame and solve highly ambiguous problems in an early-stage startup setting.

Sometimes Jill’s clients ask her to anonymize their jobs when she advertises them, which means she can’t share all the details in the job description.