Platform ML Engineer — Build End-to-End AI for Institutions

Socket.dev; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Brain Co. builds AI-native operating systems for large, regulated institutions, with Atlas at the core to keep customers in control and secure. We are extending our platform to automate complex construction documents and other workflows using agents and foundation models.

As a Machine Learning Engineer on Platform, you will own core ML capabilities end-to-end, push frontier models into production, and enable dozens of institutional workflows with reliable, measurable improvements every month.

Qualifications

• Experience turning LLMs and agentic systems into production capabilities.
• Comfortable working at the research frontier with production stakes.
• Ability to ship end-to-end platform capabilities in a fast-moving environment.

Responsibilities

• Turn pod needs into platform capabilities.
• Own capabilities end-to-end.
• Work at the research frontier with production stakes.
• Serve customers on both sides of the wall.
• Engineer for production reality.
• Raise the bar across the company.

Skills

ML engineering

LLMs

Production ML

Tools

PyTorch

TensorFlow

Job description

Brain Co. builds AI-native operating systems for large, regulated institutions, with Atlas at the core to keep customers in control and secure. We are extending our platform to automate complex construction documents and other workflows using agents and foundation models.

As a Machine Learning Engineer on Platform, you will own core ML capabilities end-to-end, push frontier models into production, and enable dozens of institutional workflows with reliable, measurable improvements every month.