Brain CoMachine Learning Engineer, Applied AI Co-Op Intern, Winter 2027
Brain Co is hiring a Machine Learning Engineer, Applied AI Co-Op Intern, Winter 2027 for a remote role open to applicants in United States. Level rates it ; you can apply on Level.
AI in this role
Design, build, and deploy machine learning and LLM-powered systems as a Machine Learning Engineer Co-Op Intern.
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 NowBrain 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 Co-Op:
As an AI/ML Engineer Co-op Intern, you’ll work alongside experienced engineers and researchers to help design, build, and deploy machine learning systems that solve high-impact problems in healthcare, government, and energy.
This internship is designed for current undergraduate students (juniors and seniors) who want hands-on experience applying modern AI techniques—especially large language models—to real-world challenges. You’ll gain exposure to the full ML lifecycle while receiving mentorship and ownership over meaningful projects.
What You’ll Do
Assist in designing and deploying LLM-powered applications to automate complex, real-world workflows
Build and improve data pipelines and support model training, evaluation, and optimization
Work with structured and unstructured data (e.g., text, documents, logs)
Help prepare models and systems for production deployment and monitoring
Collaborate closely with senior engineers, AI researchers, and product teams
Learn best practices through code reviews, design discussions, and hands-on mentorship
Gain exposure to customer-facing and real-world constraints, including working with public-sector institutions
You Might Be a Good Fit 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 programming in Python
Have coursework or project experience in machine learning or AI
Have exposure to or interest in large language models and GenAI applications (e.g., agents, RAG, reasoning workflows)
Have used or are eager to learn frameworks such as PyTorch, JAX, or TensorFlow
Have strong fundamentals in data structures and algorithms
Are curious, proactive, and excited to learn quickly in a fast-paced environmentEnjoy owning problems end-to-end with guidance and support
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)
How we rate this
Machine Learning Engineer, Applied AI Co-Op Intern, Winter 2027 at Brain Co rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $199k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where model training was part of your work. What did you do?
- Tell me about a project where evaluation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, Machine learning, Data Pipelines, Model Training, and Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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