ML Platform Engineer — Build Institutional AI

Brain Co.; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Brain Co. builds AI‑native operating systems for large, regulated institutions.

Its Atlas platform powers agents that read policy stacks to financial filings, enabling secure, scalable automation across construction, insurance, health and financial services. As a Machine Learning Engineer on Platform, you’ll craft core ML capabilities—extraction, model routing, and improved feedback loops—used across products.

Responsibilities

• Turn pod needs into platform capabilities — find the general capability inside one team's specific, urgent request, without over‑abstracting before the pattern is proven.
• Own capabilities end‑to‑end. There is no handoff: whoever builds the capability owns its behavior in production, across every deployment that uses it.
• Work at the research frontier with production stakes, turning LLMs, RL fine‑tuning, and agentic systems into capabilities that dozens of institutional workflows depend on at once.
• Serve customers on both sides of the wall — project pods as true customers, and when needed, the domain experts whose decisions your capabilities ultimately power.
• Engineer for production reality, navigating accuracy, latency, cost, and reliability across environments far messier than any benchmark.
• Raise the bar across the company. The platform is how learnings travel: what one pod discovers, you turn into something every pod inherits.

Job description

Brain Co. builds AI‑native operating systems for large, regulated institutions.

Its Atlas platform powers agents that read policy stacks to financial filings, enabling secure, scalable automation across construction, insurance, health and financial services. As a Machine Learning Engineer on Platform, you’ll craft core ML capabilities—extraction, model routing, and improved feedback loops—used across products.