Machine Learning Engineer, Applied AI @ Brain Co.
Brainco
San Francisco, CAOn-siteFull-time$140k – $220k / year
About this role
Machine Learning Engineer, Applied AI @ Brain Co.
- Back to Brain Co.’s Job Listings
Machine Learning Engineer, Applied AI
Location
San Francisco Bay Area
Employment Type
Full time
Location Type
Hybrid
Department
Engineering
Our Mission
Rebuild how the world works, to make institutions work better for the people they serve.
About Brain Co.
Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.
Why Now
Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.
Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.
You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.
About The Role
As a Machine Learning Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential.
In This Role, You Will:
Innovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.
Optimize and Scale: Build scalable data pipelines, optimize mo
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