We have an open headcount on my team at Databricks (Compute Lifecycle) for a senior or staff engineer! Typically this means 5+ years of experience. For this role, we're also looking for experience with distributed systems (and ideally experience running Kubernetes at scale). Our team maintains several systems that automate cluster provisioning at scale and allow us to manage hundreds of Kubernetes clusters that power Databricks' serverless products across all 3 major clouds. This includes heavy collaboration with MosaicML to support our new GenAI products. Tech stack wise, we primarily use Go (for Kubernetes facing components) and Scala for Databricks' internal services.
Remote Conditions
Applicants must be able to commute to one of the San Francisco or Mountain View offices at least two days a week.
Founded in late 2020 by a small group of machine learning engineers and researchers, MosaicML enables companies to securely fine-tune, train and deploy custom AI models on their own data, for maximum security and control. Compatible with all major cloud providers, the MosaicML platform provides maximum flexibility for AI development. Introduced in 2023, MosaicML’s pretrained transformer models have established a new standard for open source, commercially usable LLMs and have been downloaded over 3 million times. MosaicML is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all. Now part of Databricks since July 2023, we are passionate about enabling our customers to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI platform so our customers can use deep data insights to improve their business. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.