Senior Data Scientist/Machine Learning Engineer
Databricks
Job highlights
Summary
Join Databricks' Machine Learning Practice team, a specialized customer-facing team focused on Large Language Model (LLM) solutions. We deliver professional services, helping customers build, scale, and optimize ML pipelines. The team collaborates cross-functionally and seeks individuals with strong, unique specializations in LLMs, MLOps, and ML. This remote role involves developing LLM solutions, building and optimizing customer data science workloads, advising data teams, presenting at conferences, and mentoring. We look for candidates with experience in Generative AI, production-grade ML deployments, and strong communication skills. Databricks offers a competitive compensation package including base salary, bonus, equity, and benefits.
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
Preferred Qualifications
Experience working with Databricks & Apache Spark to process large-scale distributed datasets
Benefits
- Annual performance bonus
- Equity
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