Staff Software Engineer - GenAI Performance and KernelActive$191K

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.

What you'll do

• Lead the design, implementation, benchmarking, and maintenance of core: compute kernels (e.g. attention, MLP, softmax, layernorm, memory management) optimized for various hardware backends (GPU, accelerators)

• Drive the performance roadmap for kernel-level improvements: vectorization, tensorization, tiling, fusion, mixed precision, sparsity, quantization, memory reuse, scheduling, auto-tuning, etc.

• Integrate kernel optimizations with higher-level ML systems

• Build and maintain profiling, instrumentation, and verification tooling to: detect correctness, performance regressions, numerical issues, and hardware utilization gaps

• Lead performance investigations and root-cause analysis on inference: bottlenecks, e.g. memory bandwidth, cache contention, kernel launch overhead, tensor fragmentation

• Establish coding patterns, abstractions, and frameworks to modularize kernels: for reuse, cross-backend portability, and maintainability

What they're looking for

• Influence system architecture decisions to make kernel improvements more: effective (e.g. memory layout, dataflow scheduling, kernel fusion boundaries)
• Mentor and guide other engineers working on lower-level performance, provide: code reviews, help set best practices
• Collaborate with infrastructure, tooling, and ML teams to roll out: kernel-level optimizations into production, and monitor their impact
• BS/MS/PhD in Computer Science, or a related field