# Staff Software Engineer - GenAI inference Source: https://realanalystjobs.com/job/staff-software-engineer-genai-inference-databricks-ddbb7883 Staff Software Engineer - GenAI inference at Databricks, an on-site role based in San Francisco, California, USA. Experience level: 6+ Years. Pay stated in the posting: $190,900 to $232,800. Posted on 8 October 2025, read from Databricks' own careers page (Greenhouse), which RealAnalystJobs re-checks daily and removes the role when it closes. Databricks has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role). Updated 15 November 2026. ## Key facts - Company: [Databricks](https://realanalystjobs.com/companies/databricks) - Location: San Francisco, California, USA - Work mode: On-site - Pay stated in the posting: $190,900 to $232,800 - Posted: Oct 8, 2025 - Employment type: Full time - Experience level: 6+ Years - Source: Databricks' careers page (Greenhouse), re-checked daily ## Visa sponsorship The posting does not say. Databricks had H-1B petitions approved for 467 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/databricks#h1b-record) ## About this role P-1285 About This Role As a staff software engineer for GenAI inference, you will lead the architecture, development, and optimization of the inference engine that powers Databricks Foundation Model API.. You’ll bridge research advances and production demands, ensuring high throughput, low latency, and robust scaling. Your work will encompass the full GenAI inference stack: kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems. What You Will Do • 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 What We Look For • 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 Pay Range Transparency 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. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Local Pay Range $190,900 - $232,800 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Description from Databricks' public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/staff-software-engineer-genai-inference-databricks-ddbb7883) and use Apply now there to reach the employer's application. The listing is re-checked against Databricks' careers page daily and removed when it closes. ## Databricks 7 open analyst roles on Real Analyst Jobs. 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