Applied AI ML Engineer — Production Systems for Institutions

Brain Co.; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Brain Co. is building AI-native operating systems for large, regulated institutions. Our machines translate complex documents and policy stacks into production-ready decision systems, applying LLMs, agentic components, and rule engines to hard problems.

As a Machine Learning Engineer, you will own end-to-end pipelines from problem framing to deployment, collaborating with a team drawing from Palantir, Google, Meta, and Nvidia alumni. Expect frontier challenges and measurable real-world impact.

Qualifications

• Deep understanding of how machine learning actually works beyond tooling.
• Experience with modern AI, frontier models, and distributed systems.

Responsibilities

• Turn ambiguity into shipped systems—from no problem statement to production deployments.
• Own AI systems end-to-end with no handoff.
• Work at the research frontier with production stakes using LLMs and RL fine-tuning.
• Collaborate with institutions to understand decision-making and ensure systems change how work gets done.
• Engineer for production reality, balancing accuracy, latency, and cost.
• Raise the bar through design reviews and shared playbooks for AI systems trustworthy by institutions.
• Build composite AI systems and ensure proper credit assignment across components.
• Develop evaluation as a product discipline with robust failure-mode taxonomies.

Skills

ML fundamentals

Loss functions

Generalization

Evaluation

Prompting

Fine-tuning

Tool use

LLMs

Agentic systems

Job description

Brain Co. is building AI-native operating systems for large, regulated institutions. Our machines translate complex documents and policy stacks into production-ready decision systems, applying LLMs, agentic components, and rule engines to hard problems.

As a Machine Learning Engineer, you will own end-to-end pipelines from problem framing to deployment, collaborating with a team drawing from Palantir, Google, Meta, and Nvidia alumni. Expect frontier challenges and measurable real-world impact.