Machine Learning Engineer

AboutWe often joke that Fintool is "Warren Buffett as a Service." After Nicolas sold his previous startup—a legal search engine powered by AI—he invested part of the proceeds into BRK stocks, trusting in Buffett's approach. Yet, with over a decade in AI, he couldn't shake one question: Could a sophisticated language model replicate Warren Buffett's investment process?
Warren Buffett's letters, biographies, and investment decisions provide a wealth of knowledge about how to find, analyze, and understand companies. There are even textbooks on value investing that detail the step-by-step process.
What if we could break down Buffett's process into individual tasks and use an AI agent to replicate his approach? At Fintool, we took on that challenge. We deconstructed most of the tasks that Buffett performs to analyze a business—reading SEC filings, understanding earnings, evaluating management decisions—and we built an AI financial analyst to handle these tasks with precision and scale.
Job DescriptionYour challenge is to develop a high-quality, low-latency retrieval augmented generation (RAG) on top of millions of complex documents. You will lead the implementation of custom embeddings, rankers, and hybrid search.
Requirements: Python, Machine Learning (embeddings, ranking, recommendations), LLM. Knowing Spark, Databricks, and Typescript is a plus.
Experience: 3+ years
Location: San Francisco (no remote)
Contract: Full-time
Apply via the form below

#J-18808-Ljbffr