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BCBrain Co. logo

Brain Co.

San Francisco Bay Area

AI Product Engineer Co-Op Intern, Winter 2027.

INTERNSHIPREMOTEINTERNDATA & ML

Our Mission

Rebuild how the world works, to make institutions work better for the people they serve.

About Brain Co.

Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.

Why Now

Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.

Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.

You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.

About the Role

As an AI Product Intern, you will work closely with engineers, researchers, and product leaders to help design, build, and deploy AI-powered software solving real-world problems. This is a highly hands-on role where you’ll gain exposure to the full product lifecycle, from understanding customer needs to shipping production-grade AI applications.

You’ll contribute directly to live projects used by governments, healthcare systems, and industrial partners, while learning how cutting-edge AI is turned into real, scalable products.

In This Role, You Will:

Build & Ship Real Products: Support the design and development of AI-powered features across front-end, back-end, and data workflows. Help prototype and ship internal tools and customer-facing applications using modern web technologies

Learn Product + Engineering in Practice: Work with product managers and engineers to translate customer problems into clear product requirements. Gain exposure to how AI models are integrated into real-world software systems

Collaborate Closely: Partner with engineers, researchers, and operators to test, iterate, and improve AI-driven workflows. Participate in design discussions, sprint planning, and code reviews

Optimize & Improve: Assist with improving performance, reliability, and usability of deployed applications. Help analyze data, evaluate AI outputs, and iterate based on real customer feedback

Make a Real Impact: Contribute to projects modernizing government workflows, improving healthcare outcomes, or optimizing critical infrastructure. See your work deployed and used by real users — not just internal demos

You Will Thrive If You:

  • Are a current undergraduate student, specifically a junior or senior, pursuing a degree in Computer Science, Machine Learning, Data Science, or a related field

  • Have experience with software development fundamentals (through coursework, internships, or personal projects).

  • Are familiar with or excited to learn technologies like Python, TypeScript, React, REST APIs, and cloud platforms

  • Are curious about AI systems, product thinking, and real-world applications of machine learning

  • Enjoy solving ambiguous problems and learning quickly in fast-paced environments

  • Communicate clearly, collaborate well, and take ownership of your work

  • Are excited to work directly on impactful problems rather than purely theoretical projects

Co-Op Details & Benefits

  • Winter / Spring Co-Op: January 11, 2027 - April 30, 2027

  • Competitive co-op compensation

  • Hands-on mentorship from experienced AI engineers and researchers

  • Opportunity to work on real production systems used globally

  • Potential return-offer consideration for future internships or full-time roles

  • Daily lunches (if onsite)

 
Pay
Not stated
Where
San Francisco Bay Area
Work
Remote
Type
Internship
Posted
9 Oct, 2026
Apply on the original postingSign in to prepare an application

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