Senior Software Engineer, AI Runtime
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will architect and evolve a managed GPU training platform. You will improve distributed training, scheduling, resilience, observability, APIs, and developer workflows; lead initiatives from design through production; support new accelerators and regions; and mentor engineers.
Requirements
- 5+ years of experience building and operating large-scale distributed systems
- Experience with GPU training infrastructure, high-performance computing, or ML systems
- Experience with PyTorch, FSDP, DeepSpeed, Megatron, or distributed training parallelism strategies
- Understanding of checkpointing, failure detection, and automatic recovery
- Knowledge of GPU architecture, NVLink, InfiniBand or RoCE, collective communication, and training performance
- Experience operating managed multi-tenant cloud platforms with SLAs and SLOs
- Knowledge of algorithms, data structures, and system design
- BS in Computer Science or a related field
Responsibilities
- Drive the architecture and evolution of the managed GPU training platform
- Solve multi-node orchestration, distributed parallelism, GPU scheduling, data loading, and checkpointing challenges
- Improve GPU utilization, training throughput, and cost efficiency
- Build resilience and observability for multi-node jobs
- Shape APIs, CLI, and developer workflows for production training jobs
- Lead engineering efforts from design through production rollout
- Support new accelerators and regions
- Mentor engineers through design reviews and technical discussions
Benefits
- Eligibility for an annual performance bonus
- Equity