Senior Staff Software Engineer, AI Runtime

Databricks · Mountain View, California; San Francisco, California · Engineering · listed October 22, 2026

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The shape of it

Seniority
Staff
Where
Not stated
Stated pay
$228,600 – $342,800 USD
Requirements listed
8
Length
827 words

In the posting’s own words

As a Senior Staff Software Engineer, you'll work on the systems behind all of this, solving the hardest technical problems and shaping where AI Runtime goes next.

What it asks for · 8

  • 15+ years in large-scale distributed systems, with significant depth in GPU training, high-performance computing, or ML systems.
  • Hands-on experience training large models with FSDP, DeepSpeed, or Megatron, and fluency in parallelism strategies.
  • Expertise in GPU performance, including accelerator architecture, high-speed interconnects, and kernels.
  • Strong understanding of training resilience patterns, such as checkpointing, failure detection, and automatic recovery.
  • A background in building and running multi-tenant cloud platforms as products.
  • A track record of setting technical direction across teams and seeing it through to business impact.
  • The credibility to bring teams to agreement on difficult trade-offs, and a reputation as a mentor senior engineers seek out.
  • BS in Computer Science or a related field (MS or PhD preferred).

What the job covers

  • Drive AI Runtime's architecture and lead Databricks' long-term technical direction in AI training infrastructure.
  • Define the reliability and observability strategy for a fleet that keeps growing in scale and complexity.
  • Shape AI Runtime's developer experience for people and agents, so even the largest training jobs feel as simple as a first experiment.
  • Anticipate industry trends and choose the technical bets that prepare AI Runtime for new GPU generations and workload types.
  • Take on the hardest multi-node training problems yourself, from orchestration and GPU scheduling to data loading and checkpointing.
  • Make training faster and cheaper by raising efficiency across model architectures and GPU accelerators.
  • Work with research, product, and customers to decide what we build next and align teams on hard technical calls.
  • Champion engineering excellence, raise the bar, and help us hire and grow great engineers.

Degree language

  • BS in Computer Science or a related field (MS or PhD preferred).

Tools and skills named

Models & research
  • GPU7×
  • Fine-tuning
  • Machine learning
Cloud & infra
  • Distributed systems
  • Observability
  • Serverless
Data
  • Databricks3×
Frameworks
  • Node.js

Words the posting leans on

  • training10×
  • models7×
  • gpu6×
  • runtime5×
  • technical5×
  • next4×
  • architecture3×
  • engineers3×
  • product3×
  • systems3×
  • accelerator2×
  • agents2×
  • already2×
  • build2×
  • checkpointing2×
  • customers2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched October 31, 2026 and last changed by Databricks on October 22, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.