Staff Software Engineer - AI Research Infrastructure

Responsibilities

• Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems)
• Build powerful abstractions for job submission, scheduling, and monitoring so researchers can go from idea to large‑scale experiment in minutes
• 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 trains, evaluates, and ships models
• Serve as a technical mentor and force multiplier for other engineers working on compute, infra, and AI systems

Requirements

• 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 building and operating distributed systems, data pipelines, or large‑scale backend services, ideally involving GPUs, clusters, or major cloud providers
• Proficient in one or more systems programming languages (e.g., C++, Rust, Go, Java, Scala) and able to design, implement, and debug complex services
• Experience building or significantly contributing to cluster schedulers, resource managers, or large‑scale job orchestration systems (e.g., Kubernetes, Slurm, Ray, custom internal systems)
• Understanding of modern ML training and inference workflows (e.g., distributed training, model parallelism, fine‑tuning, evaluation)
• Ability to move fast and be pragmatic while caring about operational excellence; experience driving complex systems from prototype to stable, well‑owned services
• Strong communication skills with both researchers and engineers