Description
At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development.
The Databricks AI Research organisation enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures.
As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research.
The Impact you will have
As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will:
- 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 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 trains, evaluates, and ships models to customers
- Serve as a technical mentor and force multiplier for other engineers working on compute, infra, and AI systems
What We Look 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
- Have deep experience with building and operating distributed systems, data pipelines, or large-scale backend services, ideally involving GPUs, clusters, or major cloud providers
- Are proficient 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), even if you’re not primarily a research scientist
- Can move fast and be pragmatic in getting things done, while caring about operational excellence
- Communicate clearly with both researchers and engineers, and enjoy translating between research needs and infra realities
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. Local Pay Range $190,000-$270,000 USD