Senior Data Scientist, Machine Learning Engineer

Summary

Join the Machine Learning (ML) Practice team at Databricks as a remote role to develop LLM solutions, build and optimize customer data science workloads, and advise data teams. The ideal candidate has experience building Generative AI applications, hands-on industry data science experience, and a graduate degree in a quantitative discipline.

Requirements

• Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI
• 5+ years of hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• 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
• Build, scale, and optimize customer data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains
• Advise data teams on various data science such as architecture, tooling, and best practices
• Present at conferences such as Data+AI Summit
• Provide technical mentorship to the larger ML SME community in Databricks
• Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap

Benefits

• Annual performance bonus
• Equity