Sr. Manager, Engineering - Model Serving

Databricks Databricks · Data AI · San Francisco, CA · Engineering

Lead the engineering team responsible for Databricks' Model Serving product, focusing on both customer-facing capabilities and foundational infrastructure for scalable, low-latency AI/ML model inference.

What you'd actually do

  1. Lead, mentor, and grow a high-performing engineering team responsible for both the customer-facing Model Serving product and its foundational infrastructure — covering runtime, APIs, scaling, reliability, and integrations.
  2. Define and own the product and technical roadmap for Model Serving, balancing customer experience, functionality, and foundational investments across deployment, inference, monitoring, and scaling.
  3. Collaborate closely with product, research, platform, and infrastructure teams to drive end-to-end delivery — from ideation and prioritization to launch and operation.
  4. Ensure Model Serving meets stringent SLAs, SLOs, and performance and reliability goals, continuously improving operational efficiency and customer experience.
  5. Drive architectural decisions and product design around latency, throughput, autoscaling, GPU/CPU placement, and cost optimization.

Skills

Required

  • 5+ years of experience in technical leadership or management.
  • Proven track record building and operating large-scale distributed systems, preferably real-time or low-latency APIs.
  • Deep understanding of real-time serving systems.
  • Experience driving architectural design and operational excellence for production systems with measurable SLAs and SLOs.
  • Familiarity with CPU/GPU performance optimization, concurrency, caching, and scalability concepts.
  • Excellent collaboration and communication skills across engineering, product, and research organizations.
  • Ability to lead teams through ambiguity and deliver complex, cross-functional projects.

Nice to have

  • Masters or PhD Preferred

What the JD emphasized

  • stringent SLAs, SLOs
  • low-latency inference
  • scalability
  • performance
  • cost optimization

Other signals

  • Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models
  • real-time, low-latency inference, governance, monitoring, and lineage
  • operationalize models at scale with strong SLAs and cost efficiency