Staff Software Engineer - AI Research Infrastructure
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will develop and run the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate and observe large-scale training and inference experiments across thousands of GPUs, improve dev tooling, and partner with research scientists, ML engineers and platform teams to turn experimental workloads into robust, repeatable pipelines.
Requirements
- BS/MS or PhD in Computer Science or related field
- 5+ years of software engineering experience, including large-scale distributed systems or infrastructure
- Deep experience building and operating distributed systems, data pipelines or large-scale backend services, ideally involving GPUs, clusters or cloud providers
- Proficiency in one or more systems programming languages (C++, Rust, Go, Java, Scala)
- Experience with cluster schedulers, resource managers or job orchestration systems (Kubernetes, Slurm, Ray)
- Understanding of ML training and inference workflows
- Clear communication with researchers and engineers
Responsibilities
- Design and implement infrastructure for large-scale experiments, data processing and model training
- Build abstractions for job submission, scheduling and monitoring so researchers can run large experiments quickly
- Create tooling that improves research developer productivity, such as experiment management and CI/testing infrastructure
- Influence the long-term roadmap for research computation
- Mentor other engineers working on compute, infra and AI systems
Benefits
- Annual performance bonus eligibility
- Equity eligibility