Early Career AI​/ML Engineer

About The Role

As an AI/ML 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.

• 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 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.

• 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 a related field.
• 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 Tensor Flow.
• 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.