Senior Staff Software Engineer, AI Runtime
$229k - $343k • Remote • Mountain View, California; San Francisco, California
Posted 8h ago
Job Location
Mountain View, California; San Francisco, California
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Infrastructure Engineer
About the job
Databricks is seeking a Senior Staff Software Engineer to work on the AI Runtime system, which powers the world's largest AI platform. This serverless product enables companies to train their own models using enterprise data, similar to how frontier labs operate. The role involves tackling complex technical challenges to advance AI Runtime's architecture, reliability, and developer experience for both humans and AI agents. You will contribute to shaping the long-term technical direction of AI training infrastructure, anticipating industry trends, and optimizing training efficiency and cost across various model architectures and GPU accelerators.
Responsibilities
- Drive AI Runtime's architecture and lead Databricks' long-term technical direction in AI training infrastructure.
- Define the reliability and observability strategy for a growing fleet of AI infrastructure.
- Shape AI Runtime's developer experience for people and agents to simplify large training jobs.
- Anticipate industry trends and make technical bets for new GPU generations and workload types.
- Solve complex multi-node training problems, including orchestration, GPU scheduling, data loading, and checkpointing.
- Improve training speed and reduce costs by increasing efficiency across model architectures and GPU accelerators.
- Collaborate with research, product, and customers to define future development and align teams on technical decisions.
- Champion engineering excellence and mentor other engineers.
Requirements
- 15+ years of experience in large-scale distributed systems, with significant depth in GPU training, high-performance computing, or ML systems.
- Hands-on experience training large models using FSDP, DeepSpeed, or Megatron, with fluency in parallelism strategies.
- Expertise in GPU performance, including accelerator architecture, high-speed interconnects, and kernels.
- Strong understanding of training resilience patterns (checkpointing, failure detection, automatic recovery).
- Experience building and running multi-tenant cloud platforms as products.
- Proven track record of setting technical direction across teams and achieving business impact.
- Credibility to facilitate agreement on difficult trade-offs and a reputation as a sought-after mentor.
- BS in Computer Science or related field (MS or PhD preferred).
Benefits
- Eligibility for annual performance bonus
- Equity
- Comprehensive benefits and perks