DatabricksSan Francisco, CABuild and optimize LLM inference infrastructure at enterprise scale for partner and self-hosted frontier models. Requires 8+ years backend/infrastructure engineering experience with distributed systems, real-time serving, and ML/GPU orchestration.
Staff Engineer responsible for designing enterprise AI platform architecture, reusable components, responsible AI controls, observability, and governance patterns. Requires deep expertise in generative AI, RAG, agentic workflows, and influencing cross-functional teams without direct authority.
Founding member of a new team building foundational evaluation infrastructure and flywheels for Databricks' AI/Genie Agents. Design scalable tooling for benchmarking, regression detection, and quality measurement that drives continuous agent improvement across research, training, and production.
Build and shape the Foundation Model API serving layer for large-scale LLM inference (partner and self-hosted models) at Databricks. Requires 8+ years backend/infra engineering experience with distributed systems, ML infrastructure, and a strong product ownership mindset.
Staff Software Engineer building and scaling Databricks' managed large-scale GPU training platform (AIR). Focus on distributed training performance, scheduling, fault tolerance, and developer experience for thousands of accelerators.
Develops and deploys state-of-the-art GenAI models and systems for Databricks products like Assistant and Genie. Requires 2-8 years ML engineering experience, proficiency in Python/PyTorch/TensorFlow, and expertise in LLMs.