Description review
Machine Learning Engineer, Applied AI Co-Op Intern, Winter 2027
Brain Co. · Remote - San Francisco Bay Area · back to the listing
HR standards
67/100
needs work
Title ↔ description
89/100
strong
Reads as
Machine Learning Engineer
100% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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- Senior AI Engineer – Notebooks Datadog
Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
- Member of Technical Staff (applied) Anthrogen
- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- 20 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
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 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 environment
• Enjoy 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)
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 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 environment
• Enjoy 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)