Machine Learning Engineer, Applied AI

The role

You will turn ambiguous problems into shipped AI systems and own AI systems end-to-end. You will work at the research frontier applying LLMs, RL fine-tuning, and agentic systems to create production decision systems for 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 stakes
• 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 how machine learning works 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 the problem, data, and definition of success 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, powers agents that drive real workflows across government, insurance, health, and financial services.