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Databricks

Staff Engineer, Model Serving

Department
Engineering
Job Type / Location
San Francisco
Experience Required
10+ years
Posted On

About the Role

As a Staff Engineer at Databricks, you will play a critical role in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform.

The Impact You Will Have

  • Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence.
  • Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
  • Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads.
  • Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale.
  • Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
  • Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers.
  • Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
  • Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

What We Look For

  • 10+ years of experience building and operating large-scale distributed systems.
  • Deep expertise in model serving, inference systems, and related infrastructure (e.g., routing, scheduling, autoscaling, and observability).
  • Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
  • Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
  • Experience leading architecture for large-scale, performance-sensitive CPU/GPU inference systems.
  • Strong communication skills and ability to collaborate across teams in fast-moving environments.
  • Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
  • Passion for mentoring, growing engineers, and fostering technical excellence.

View Assessment Process

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