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About the Role

As a Machine Learning Engineer on Platform, you'll build the core ML capabilities that every product ships with. This role offers leverage by improving foundational elements like document extraction and blueprint models, which in turn enhance all vertical products and deployed systems. You will contribute to building Atlas, our platform which includes a foundation model for construction documents, extraction agents, a unified evaluation system, and model routing.

Responsibilities

Turn pod needs into platform capabilities, identifying generalizable solutions from specific requests without premature abstraction.
Own capabilities end-to-end, including their production behavior across all deployments.
Work at the research frontier, integrating LLMs, RL fine-tuning, and agentic systems into production capabilities.
Serve both internal project pods and domain experts as customers.
Engineer for production realities, balancing accuracy, latency, cost, and reliability in complex environments.
Elevate company-wide capabilities by translating learnings from one pod into inheritable platform features.

Requirements

Understand how machine learning works, including the philosophy behind tooling, loss function optimization, generalization under distribution shift, and evaluation.
Possess deep knowledge of modern AI, with expertise in LLMs and agentic systems, including prompting, fine-tuning, tool use, and reasoning.
Be able to discern when a fine-tuned segmentation model, rule engine, or a combination of approaches is most effective.
Treat frontier models as components to be measured, optimized, and engineered.
Have a platform-oriented mindset, identifying general capabilities within specific team requests.
Understand when generalization is premature.
Treat internal teams as customers with deadlines and measure success by their velocity.
Be energized by building novel solutions where the problem, data, and success metrics are initially undefined.
Navigate accuracy, latency, cost, and reliability in production environments.

Skills

Machine Learning
LLMs
Agentic Systems
Prompting
Fine-tuning
Tool Use
Reasoning
Segmentation Models
Rule Engines
Composite AI Systems
Credit Assignment
Continuous Improvement Engineering
Document Extraction
Financial Reporting
Market Data
Model Routing
Evaluation Systems

About the Company

Brain Co. builds AI-native operating systems for large, regulated institutions.
Our systems are industry-specific and powered by agents that advance real workflows.
We utilize Atlas, our proprietary platform, ensuring customer control, security by design, and freedom from vendor lock-in.
Brain Co. is entering a new phase of national-scale production deployments.
Our team comprises talent from Palantir, Google, Meta, and Nvidia.
We are expanding our presence in government, insurance, health, and financial services.
Joining now offers the opportunity to shape the company and a new category of applied AI.
Every project ships to production and is expected to deliver measurable customer value and impact.
We foster an environment where you work alongside exceptional peers on challenging applied AI problems.