← All roles

Staff Software Engineer - GenAI inference

Databricks· Engineering
Apply on company site
San Francisco$190.9k - $232.8kfull-timePosted 11mo ago

About the role

Senior role leading architecture, development, and optimization of the GenAI inference engine powering Databricks Foundation Model API, spanning kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems.

Responsibilities

  • Own and drive the architecture, design, and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference
  • Partner closely with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine
  • Lead the end-to-end optimization for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators
  • Define and guide standards to build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations
  • Architect scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads
  • Ensure reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning
  • Collaborate cross-functionally on Integrating with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead
  • Drive cross-team collaboration: with platform engineers, cloud infrastructure, and security/compliance teams
  • Represent the team externally through benchmarks, whitepapers, and open-source contributions

Qualifications

  • BS/MS/PhD in Computer Science, or a related field
  • Strong software engineering background (6+ years or equivalent) in performance-critical systems
  • Proven track record of owning complex system components and driving architectural decisions end-to-end
  • Deep understanding of ML inference internals: attention, MLPs, recurrent modules, quantization, sparse operations, etc.
  • Hands-on experience with CUDA, GPU programming, and key libraries (cuBLAS, cuDNN, NCCL, etc.)
  • Strong background in distributed systems design, including RPC frameworks, queuing, RPC batching, sharding, memory partitioning
  • Demonstrated ability to uncover and solve performance bottlenecks across layers (kernel, memory, networking, scheduler)
  • Experience building instrumentation, tracing, and profiling tools for ML models
  • Ability to lead through influence - work closely with ML researchers, translate novel model ideas into production systems
  • Excellent communication and leadership skills, with a proactive and ownership-driven mindset
  • Bonus: published research or open-source contributions in ML systems, inference optimization, or model serving

Skills

Required:Architecture and system designCUDA and GPU programmingDistributed systemsInstrumentation, tracing, profiling

Benefits

  • Benefits information available via company page (regional details)
Last updated Sep 10, 2026. Interested? Apply on the company site.

About Databricks

Leading Data and AI Platform for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

AIanalyticsbig datadatadata warehousingenterprise-infrastructuregovernanceliquid-ai-recruiting-target
Company profileWebsite

More open roles at Databricks