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Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM

Databricks

$100,400 - $209,000
Apr 15, 2025
Remote, US
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The Machine Learning Practice team at Databricks is facing an increasing demand for Large Language Model-based solutions and needs a professional to help deliver professional services engagements to customers.

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
  • Experience working with Databricks & Apache Spark to process large-scale distributed datasets (Preferred)
  • Experience with tools such as HuggingFace, Langchain, and OpenAI
  • Experience with pandas, scikit-learn, and TensorFlow/PyTorch

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

Other

  • 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