Databricks Inc.
Software Engineer - GenAI inference
Databricks Inc., San Francisco, California, United States, 94199
As a software engineer for GenAI inference, you will help design, develop, and optimize the inference engine that powers Databricks’ Foundation Model API. You’ll work at the intersection of research and production, ensuring our large language model (LLM) serving systems are fast, scalable, and efficient. Your work will touch the full GenAI inference stack — from kernels and runtimes to orchestration and memory management.
What You Will Do
Contribute to the design and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference Collaborate with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine Optimize for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators Build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations Develop and enhance scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads Support reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning Integrate with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead Collaborate cross-functionally: with platform engineers, cloud infrastructure, and security/compliance teams Document and share learnings, contributing to internal best practices and open-source efforts when possible What We Look For
BS/MS/PhD in Computer Science, or a related field Strong software engineering background (3+ years or equivalent) in performance-critical systems Solid 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.) Comfortable designing and operating distributed systems, 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 work closely with ML researchers, translate novel model ideas into production systems Ownership mindset and eagerness to dive deep into complex system challenges Bonus: published research or open-source contributions in ML systems, inference optimization, or model serving Pay Range Transparency Local Pay Range $142,200 — $204,600 USD About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. 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, please visithttps://www.mybenefitsnow.com/databricks. 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.
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Contribute to the design and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference Collaborate with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine Optimize for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators Build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations Develop and enhance scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads Support reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning Integrate with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead Collaborate cross-functionally: with platform engineers, cloud infrastructure, and security/compliance teams Document and share learnings, contributing to internal best practices and open-source efforts when possible What We Look For
BS/MS/PhD in Computer Science, or a related field Strong software engineering background (3+ years or equivalent) in performance-critical systems Solid 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.) Comfortable designing and operating distributed systems, 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 work closely with ML researchers, translate novel model ideas into production systems Ownership mindset and eagerness to dive deep into complex system challenges Bonus: published research or open-source contributions in ML systems, inference optimization, or model serving Pay Range Transparency Local Pay Range $142,200 — $204,600 USD About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. 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, please visithttps://www.mybenefitsnow.com/databricks. 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.
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