Related skills
distributed systems observability autoscaling gpu model serving📋 Description
- Design and implement core systems and APIs powering Model Serving.
- Drive architecture decisions to optimize CPU/GPU performance and autoscaling.
- Contribute to components across serving infra: containers, routing, observability.
- Collaborate with product, platform, and research teams to build reliable systems.
- Lead technical initiatives to improve latency, availability, and cost.
- Establish best practices for code quality, testing, and readiness; mentor engineers.
🎯 Requirements
- 5+ years building and operating large-scale distributed systems.
- Experience in model serving, inference systems, or related infra (routing, autoscaling).
- Strong foundation in algorithms, data structures, and system design for low-latency serving.
- Proven ability to deliver technically complex, high-impact initiatives with measurable value.
- Experience architecting large-scale CPU/GPU inference systems.
- Strong communication and collaboration across teams in fast-moving environments.
🎁 Benefits
- Pay range transparency is provided; see the pay zone mapping page.
- Benefits vary by region; visit the Databricks benefits site for details.
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