Role at a glance
- Salary
- $192K – $260K/yr
- Location
- San Francisco, California, United States Mountain View, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 10+ years of experience building and operating large-scale distributed systems.
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Role Summary
The Staff Engineer will shape the product experience and core infrastructure for Databricks Foundation Model Serving, an API product for hosting and serving inference for open source and proprietary frontier AI models. The role focuses on building high-throughput, low-latency GPU serving systems and influencing the architecture of a foundation model API product through collaboration across platform, product, infrastructure, and research teams.
What You'll Do
- Design and implement core systems and APIs that power Databricks Foundation Model Serving.
- 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 GPU...
- Contribute to serving infrastructure components, including systems such as vLLM and SGLang, token based rate limiters, and optimizers.
- Collaborate with product, platform, and research teams to translate customer needs into reliable and performant systems.
- Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
10+ years of experience building and operating large-scale distributed systems; experience leading high-scale operationally sensitive backend systems; strong foundation in algorithms, data structures, and system design; ability to deliver technically complex, high-impact initiatives; strong communication and cross-team collaboration skills; strategic and product-oriented mindset.
Required
- 10+ years of experience building and operating large-scale distributed systems
- Experience leading high-scale operationally sensitive backend systems
- A track record of up-leveling teams engineering excellence
- 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
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
Foundation Model Serving is the API Product for hosting and serving frontier AI model inference for open source models like Llama, Qwen, and GPT OSS as well as proprietary models like Claude and OpenAI GPT. For this role, no prior ML or AI experience is necessary. We’re looking for engineers who have owned high scale operational sensitive systems like customer facing APIs, Edge Gateways, ML Inference, or similar services and have an interest in getting deep building LLM APIs and runtimes at scale.
As a Staff Engineer, you’ll play a critical role in shaping both the product experience and core infrastructure. You will design and build systems that enable high-throughput, low-latency inference on GPU workloads with frontier models, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class foundation model API product.
The impact you will have:
- Design and implement core systems and APIs that power Databricks Foundation 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 GPU serving workloads.
- Contribute directly to key components across the serving infrastructure — from working in systems like vLLM and SGLang to creating token based rate limiters and optimizers — 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.
- 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.
- Experience leading high-scale operationally sensitive backend systems.
- A track record of up-leveling teams engineering excellence.
- 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.
- 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.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.