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Databricks Software Engineer Jobs (NOW HIRING)

Databricks

Staff Software Engineer - Money Team

Bellevue, WA · On-site

$182.40K - $247K/yr

Staff Software Engineer - Money Team P-940 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this ...

Databricks

Senior Software Engineer - Backend

Bellevue, WA · On-site +1

$138.30K - $182.30K/yr

P-939 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are ... As a software engineer with a backend focus, you will work with your team to build infrastructure ...

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Databricks Software Engineer information

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How much do databricks software engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for databricks software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.
Infographic showing various Databricks Software Engineer job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
Staff Software Engineer - AI Research Infrastructure

Staff Software Engineer - AI Research Infrastructure

Databricks

New York, NY • On-site

$189.30K - $224.30K/yr

Other

Posted 28 days ago

Job description

Staff Software Engineer - AI Research Infrastructure

P-1215

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization 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. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company's AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description

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 largescale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security.

You'll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support.

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 largescale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloudbased systems)
  • Enable researchers to go from idea to largescale 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 longterm 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 Look for

  • BS/MS or PhD in Computer Science or related field
  • 5+ years of software engineering experience, including substantial time working on largescale distributed systems or infrastructure.
  • Have deep experience with building and operating distributed systems, data pipelines, or largescale 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 largescale job orchestration systems (e.g., Kubernetes, Slurm, Ray, custom internal systems).
  • Understand modern ML training and inference workflows (e.g., distributed training, model parallelism, finetuning, 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. Have driven complex systems from prototype to stable, wellowned services.
  • Communicate clearly with both researchers and engineers, and enjoy translating between research needs and infra realities.

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