AI Engineer, AI FDE
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
About the Role
You will build LLM solutions on customer data, such as RAG architectures, natural-language querying of structured data and content generation. You will build, scale and productionize data science workloads with MLOps, advise data teams, present at conferences, mentor others and work with product and engineering on the roadmap. The role can be remote.
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 with pandas, scikit-learn, and TensorFlow/PyTorch
- Experience building production-grade ML deployments on AWS, Azure or GCP
- Graduate degree in a quantitative discipline or equivalent practical experience
- Experience communicating and teaching technical concepts
- Preferred: experience with Databricks and Apache Spark
Responsibilities
- Develop LLM solutions on customer data such as RAG architectures, text-to-SQL and content generation
- Build, scale and optimize customer data science workloads and apply MLOps to productionize them
- Advise data teams on architecture, tooling and best practices
- Present at conferences such as Data+AI Summit
- Provide technical mentorship to the ML SME community
- Collaborate with product and engineering to define priorities and influence the roadmap