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.
At Brain Co., new-grad engineers contribute to real production systems and see their work deployed at global scale.
About the RoleAs a Machine Learning Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential.
What You’ll Work OnInnovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.
Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide.
Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large.
Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills.
Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices.
Expect to complete a bachelor’s degree in Computer Science, Engineering, Machine Learning, Data Science, or a related field in Spring 2027.
Have hands-on experience building GenAI-focused applications (e.g., agents, reasoning workflows, or RAG) and a solid understanding of how large language models are architected and operated.
Have personally implemented models in common ML frameworks such as PyTorch, Jax or TensorFlow.
Possess a strong foundation in data structures, algorithms, and software engineering principles.
Exhibit excellent problem-solving and analytical skills, with a proactive approach to challenges.
Can work collaboratively with cross-functional teams.
Thrive in fast-paced environments where priorities or deadlines may compete.
Are eager to own problems end-to-end and willing to acquire any necessary knowledge to get the job done.
Eligibility: Completing a bachelor’s degree in Spring 2027.
Competitive full-time compensation and benefits
Support and feedback from experienced platform engineers
Opportunity to work on real production systems used globally
Meaningful ownership from day one, with room to grow alongside the team
Daily lunches (if onsite)
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