Machine Learning Engineer, Applied AI

The role

You will build and own AI systems end-to-end, from ambiguous customer problems to production deployments. You will work on composite AI systems, document understanding, and agentic systems for regulated institutions.

What you will do

• Turn ambiguity into shipped systems.
• Own AI systems end-to-end from training to production behavior.
• Apply LLMs, RL fine-tuning, and agentic systems to production tasks.
• Work directly with institutions to understand decision-making processes.
• Engineer for production reality including accuracy, latency, cost, and reliability.
• Raise the bar through design reviews and an internal paper club.

Required qualifications

• Understand machine learning philosophy including loss functions, generalization, and distribution shift.
• Have instincts for prompting, fine-tuning, tool use, and reasoning with LLMs and agentic systems.
• Know when to use fine-tuned segmentation models, VLMs, or rule engines.
• Be energized by building things that have never existed.
• Be comfortable when problems, data, and success definitions must be invented.

Benefits

• Meaningful equity
• Country-specific benefits

About the company

Brain Co. builds AI-native operating systems for large, regulated institutions. Their platform, Atlas, uses agents to power workflows across government, insurance, health, and financial services.