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Machine Learning Engineer, Applied AI

Brain Co.· Engineering
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Hybrid (San Francisco Bay Area)Full-timePosted 11mo ago

About the role

Machine Learning Engineer role focused on building production-ready, end-to-end AI systems for regulated institutions, applying frontier ML techniques (LLMs, agentic systems, RL fine-tuning) to production decision-making pipelines across domains like construction permitting, insurance, and healthcare.

Responsibilities

  • Turn ambiguity into shipped systems — from no problem statement, no labeled data, and no agreed definition of success, to well-posed ML problems and production deployments.
  • Own AI systems end-to-end. There is no handoff: the person who trains the model owns its behavior in production.
  • Work at the research frontier with production stakes, applying LLMs, RL fine-tuning, and agentic systems where the output is a decision an institution acts on.
  • Work directly with the institutions we serve — permit reviewers, underwriters, compliance officers — to understand how decisions actually get made and ensure your systems change how the work gets done.
  • Engineer for production reality, navigating accuracy, latency, cost, and reliability in environments far messier than any benchmark.
  • Raise the bar across the company through design reviews, internal paper club, and the shared playbook for AI systems institutions can trust.

Qualifications

  • Understanding of how machine learning works beyond tooling (loss functions, generalization, distribution shift, evaluation).
  • Experience with modern AI techniques, prompting, fine-tuning, tool use, and reasoning for LLMs and agentic systems.
  • Ability to compose multiple components (segmentation models, VLMs, rule engines) into an accurate system.
  • Comfort building systems where problem definitions and success criteria are invented.
  • Interest in building production-grade AI systems that impact real workflows.

Skills

Required:End-to-end AI system ownershipMulti-component integration (vision, language, rule engines)Prompting, fine-tuning, tool use, reasoning with LLMs

Benefits

  • Not specified in the job description
Last updated Oct 1, 2026. Interested? Apply on the company site.

About Brain Co.

AI for the world's most important institutions

Building an AI platform and applications to deliver impact for real-world problems.

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