Senior Software Engineer - Compute Infrastructure

1w1 week ago

Databricks

San Francisco, US · Full-time · $164,200 – $205,200

About this role

At Databricks, we build and run the world's best data and AI infrastructure platform to help data teams solve tough problems. The Compute Infrastructure organization powers all Data, AI, and stateful workloads across major clouds. It launches tens of millions of VMs per day and operates thousands of Kubernetes clusters with extreme elasticity, reliability, and cost efficiency.

As a Senior Software Engineer on the Compute Infra team, you design and build systems that enable engineers to launch and scale world-class products. You develop compute abstractions providing powerful capabilities for all Databricks workloads. These efforts deliver high velocity and best-in-class performance.

You design workload orchestration and scheduling systems for serving, batch, stateful, and GPU workloads with high performance and efficiency. You scale fleet management systems that launch and configure millions of VMs across cloud providers. The team focuses on strong design practices, testing, and engineering excellence.

You raise the technical and operational bar through a platform mindset. You lead cross-team initiatives spanning product and infrastructure areas. This role offers opportunities to tackle technical challenges at massive scale.

Requirements

BS (or higher) in Computer Science or related field
5+ years of experience designing and building large-scale distributed systems
Strong proficiency in one or more languages such as Java, Scala, Go, or C++
Experience with service-oriented architectures and large scale distributed systems
Familiarity with cloud platforms (AWS, Azure, GCP) and container/orchestration technologies (Kubernetes, Docker)
Track record of shipping infrastructure that supports mission-critical workloads at scale

Responsibilities

Develop compute abstractions that provide powerful capabilities for all Databricks workloads, enabling high velocity and best-in-class performance
Design workload orchestration and scheduling systems that handle serving, batch, stateful, and GPU workloads with high performance and efficiency
Scale fleet management systems that launch and configure millions of VMs every day across cloud providers
Raise the technical and operational bar through strong design practices, testing, and a culture of engineering excellence
Lead cross-team initiatives that span product and infrastructure surface areas