Early Career Machine Learning Engineer, Applied AI
Technologies
LLM · PyTorch · Jax · TensorFlow · RAG · agents · reasoning workflows · data pipelines
About Brain Co.
Builds a shared AI platform and vertical applications for governments and large enterprises to automate high-stakes workflows in permitting, healthcare, insurance, supply chain, and customer operations.
Series A
Job description
The full responsibilities and requirements are on the employer’s site.
Open application page ↗Source and classification
Internal deployment & tooling · Evidence for this classification:
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 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. In This Role, You Will: Innovate 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
More from the job description
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 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 signif [... source excerpt omitted ...] omplex, 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 gov [... source excerpt omitted ...] 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. You Might Thrive In This Role If You: Have 0-2 years of industry experience in applied machine learning or related AI work. Hold a BSc/Master’s/PhD degree in Computer Science, Machine Learning, Data Science, or
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