About the job
As a Staff Engineer, you’ll 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.
Responsibilities
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.
Qualifications
Minimum
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.
Preferred
No preferred qualifications listed.