Staff Software Engineer - AI Research Infrastructure

Job title: Staff Software Engineer - AI Research Infrastructure

About the Role As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large-scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling, and ensure researchers can iterate quickly without sacrificing reliability, efficiency, or security.

What You'll Do

• Design and implement infrastructure that supports large-scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud-based systems).
• Enable researchers to go from idea to large-scale experiment in minutes, not days, by building abstractions for job submission, scheduling, and monitoring.
• Create tooling that improves research developer productivity, such as experiment management systems, CI/testing infrastructure for research code, and workflows that reduce iteration time.
• Influence the long-term roadmap for research computation, shaping how Databricks AI Research train, evaluate, and ship models to customers.
• Serve as a technical mentor and force multiplier for other engineers working on compute, infra, and AI systems.

What We're Looking For

• BS/MS or PhD in Computer Science or related field
• 5+ years of software engineering experience, including substantial time working on large-scale distributed systems or infrastructure
• Deep experience with building and operating distributed systems, data pipelines, or large-scale backend services, ideally involving GPUs, clusters, or major cloud providers
• Proficiency in one or more systems programming languages (e.g., C++, Rust, Go, Java, Scala) and can design, implement, and debug complex services
• Have built or significantly contributed to cluster schedulers, resource managers, or large-scale job orchestration systems (e.g., Kubernetes, Slurm, Ray, custom internal systems)
• Understand modern ML training and inference workflows (e.g., distributed training, model parallelism, fine-tuning, evaluation)
• Can move fast and be pragmatic in getting things done, while caring about operational excellence
• Have driven complex systems from prototype to stable, well-owned services
• Communicate clearly with both researchers and engineers, and enjoy translating between research needs and infra realities

Compensation & Benefits

• Local Pay Range $190,000—$270,000 USD. The total compensation package may also include eligibility for annual performance bonus, equity, and the benefits listed above. For location-based details, visit the company page.