Databricks
This role involves driving the architecture and long-term technical direction of Databricks' AI Runtime platform, focusing on AI training infrastructure and GPU performance. The position requires leading reliability strategies, enhancing developer experience, and solving complex multi-node training challenges to improve efficiency and scalability. The engineer will collaborate with research and product teams to shape future developments and mentor senior engineers.
Headquarters
San Francisco, California, United States
Company Size
5001-10000 employees
Founded
2013
Databricks is a unified Data Intelligence Platform that helps organizations build, deploy, and manage data, analytics, and AI at scale. Built on Apache Spark and Delta Lake, it provides a “lakehouse” architecture that combines data engineering, ETL, data warehousing, streaming, and machine learning (including MLflow and feature store) in a single managed service. The platform includes collaborative notebooks, scalable compute across major clouds, and built‑in governance, security, and performance optimizations. Enterprises use Databricks to simplify data pipelines, accelerate model development with a data‑centric approach, and operationalize analytics and AI.
Accenture and Databricks Accelerate Enterprise Adoption of AI Applications and Agents at Scale
2 days ago
News | AI darling Databricks further expands its downtown San Francisco headquarters
14 hours ago
S.F. tech company expands its footprint as leasing surge lifts downtown office market
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Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Databricks.
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