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).
• Enable researchers to go from idea to large-scale experiment in minutes by building powerful 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.

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 with 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 (C++, Rust, Go, Java, Scala) and can design, implement, and debug complex services.
• Built or significantly contributed to cluster schedulers, resource managers, or large-scale job orchestration systems (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 while caring about operational excellence; driven complex systems from prototype to stable services.
• Communicate clearly with researchers and engineers.