Senior Software Engineer, Model Serving
Databricks, San Francisco, California +1
- Pay
- $166K–$225K / year
- Work type
- Not stated
- Level
- Senior
- Area
- Inference & ML systems, ML / AI engineering
- Posted
- Oct 14, 2025
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About the role
P-1428
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.
As a Senior 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.
Check out our recent blog post: AI Serving Platform That Adapts to Your Model
The impact you will have:
- Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence.
- 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.
What we look for:
- 5+ years of experience building and operating large-scale distributed systems.
- Experience in model serving, inference systems, or 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 building architecture for large-scale, performance-sensitive CPU/GPU inference systems.
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Listed on Databricks's Greenhouse job board; checked 36 min ago. First seen by us 35 h ago. Being listed doesn't mean the team is actively interviewing. We found this board in a public directory and haven't yet confirmed it against the company's own careers page.