Job Location : New York,NY, USA
Join to apply for the AI Engineer - San Francisco role at Distyl AI
Join to apply for the AI Engineer - San Francisco role at Distyl AI
Distyl AI develops AI native technologies for humans & AI to collaborate to power the operations of the Global Fortune 1000.In just 24 months, we've rapidly grown to partner with some of the world's largest enterprises—including F100 telecom, healthcare, manufacturing, insurance, and retail companies—delivering multiple AI deployments with $100M+ impact. Our platform, Distillery, along with our team of AI Engineers, Researchers, and Strategists, is pioneering AI-native systems of work, solving the most complex, high-stakes challenges at scale.Distyl is founded and led by proven leaders from companies like Palantir, Apple, and top national laboratories. We work in deep partnership with OpenAI, jointly going-to-market at the largest enterprises and collaborating evaluating and testing the latest models. Backed by Lightspeed, Khosla, Coatue, industry leaders like Nat Friedman (former GitHub CEO), as well as board members of over 20+ F500s, Distyl is building the future of AI-powered enterprise operations.What We Are Looking ForAs an AI Engineer at Distyl, you'll be responsible for designing, implementing, and deploying AI-powered systems into production for some of the most iconic institutions in the world. You'll partner closely with customers to understand their most critical challenges and deliver innovative, reliable solutions that harness the power of Large Language Models (LLMs). You'll also contribute to the evolution of our internal platform, Distillery, shaping how enterprise-grade LLM applications are built and deployed.You'll be expected to bring technical depth, a builder's mindset, and an obsession with quality and performance. You will work at the cutting edge of LLMs, evaluation models, designing responsible AI solutions, and implementing them into customer environments with speed and precision. You'll also help evolve Distyl's engineering best practices, bringing the discipline needed to scale.This role requires strong software engineering skills, deep familiarity with machine learning workflows, and a bias toward practical, high impact solutions.Key Responsibilities
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