Data Scientist II

Summary

Join the highly specialized Machine Learning (ML) Practice team at Databricks, a customer-facing team focusing on Large Language Model (LLM)-based solutions. The team delivers professional services engagements to help customers build, scale, and optimize ML pipelines and put them into production. Collaborate cross-functionally with engineering, product, and developer relations teams, and support internal subject matter expert (SME) teams. This role involves developing LLM solutions on customer data, advising data teams on best practices, and providing thought leadership. The ideal candidate will have experience in building Generative AI applications and production-grade ML deployments. This role can be remote.

Requirements

• Experience in building Generative AI applications, including RAG, agents, Text2SQL, fine-tuning, and deploying LLMs, using tools such as HuggingFace, Langchain, and OpenAI
• 4 to 8 years of hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, MLflow, scikit-learn, and PyTorch
• Experience in building production-grade ML or GenAI deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience in communicating and teaching technical concepts to both non-technical and technical audiences
• Passion for collaboration, life-long learning, and driving business value through ML

Responsibilities

• Develop LLM solutions on customer data, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation
• Help customers solve tough problems across industries like Health and Life Sciences, Finance, Retail, Startups, and many others
• Build, scale, and optimize customer data science workloads across industries and apply best-in-class MLOps to productionize these workloads
• Advise data teams on data science architecture, tooling, and best practices
• Provide thought leadership by presenting at conferences such as Data+AI Summit and mentoring the larger ML SME community in Databricks
• Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap

Preferred Qualifications

Experience working with Databricks and Apache Spark™