Sr. Manager of Engineering to lead teams building the Databricks AI Gateway, an enterprise control plane for governing, routing, and monitoring LLM endpoints, coding agents, and model serving endpoints. The role involves launching and growing new products, focusing on standardizing, securing, and observing LLM inference traffic while managing cost, performance, and quality.

Software Engineer focused on designing, developing, and optimizing the inference engine for Databricks' Foundation Model API. The role involves working on the full GenAI inference stack, including kernels, runtimes, orchestration, and memory management, to ensure fast, scalable, and efficient LLM serving systems.

Hiring experienced machine learning platform engineers to build out a customer-facing generative AI platform for the ML development lifecycle, including data generation, training, evaluation, serving, and agent-building. The role involves end-to-end ownership, translating user requirements into product interfaces, and building backend distributed systems. Responsibilities span from user-facing features to low-level GPU orchestration.

Staff Software Engineer focused on building and operating the AI research infrastructure at Databricks. This role involves designing and implementing services for large-scale training and inference workloads, improving developer tooling, and ensuring reliability, efficiency, and security for AI research. The engineer will partner with researchers and ML engineers to create robust pipelines and influence the long-term roadmap for research computation.

Staff Software Engineer focused on building and operating the AI research infrastructure at Databricks. This role involves designing and implementing services for large-scale training and inference workloads, improving developer tooling, and ensuring reliability, efficiency, and security for AI research. The engineer will partner with researchers and ML engineers to create robust pipelines and influence the long-term roadmap for research computation.

Staff Backend Software Engineer for Databricks' AI Platform, focusing on Foundation Model Serving. The role involves designing and implementing high-throughput, low-latency inference systems for frontier AI models on GPU workloads, optimizing serving infrastructure, and influencing the technical roadmap for LLM APIs and runtimes at scale. Prior ML/AI experience is not required, but experience with large-scale distributed systems and operational sensitive systems is critical.

Databricks is seeking a Staff Backend Software Engineer for their AI Platform team, focusing on the Model Serving product. The role involves designing and building systems for high-throughput, low-latency inference across CPU and GPU workloads, optimizing performance, and ensuring scalability and reliability. The engineer will contribute to core serving infrastructure, collaborate cross-functionally, and lead technical initiatives to improve latency, availability, and cost-effectiveness.

Staff Backend Software Engineer for Databricks' AI Platform, focusing on the Model Serving product. The role involves designing and building scalable, low-latency inference systems for both CPU and GPU workloads, optimizing performance, and ensuring operational excellence. Key responsibilities include developing core serving infrastructure, driving architectural decisions, and collaborating across teams to deliver a world-class serving platform for enterprise AI/ML models.

Staff Backend Software Engineer for Databricks' AI Platform team, focusing on building and improving the infrastructure that powers AI offerings like MLflow, AI Gateway, Agent Framework, and Foundation Model APIs. The role involves improving reliability, latency, and efficiency of distributed AI workloads and collaborating with various teams to deliver seamless end-to-end AI experiences.

Staff Backend Software Engineer on the AI Platform team at Databricks, responsible for building and improving LLM infrastructure, including model serving, agent support, and Vector Search, to power customer AI workloads.

Staff Software Engineer focused on building and operating high-scale, low-latency inference systems for foundational AI models (LLMs) at Databricks. The role involves designing and implementing core systems and APIs for model serving, optimizing performance on GPU workloads, and influencing architectural direction for the Foundation Model Serving product.

Lead the engineering team responsible for Databricks' Model Serving product, focusing on both customer-facing capabilities and foundational infrastructure for scalable, low-latency AI/ML model inference.

Databricks is seeking a Senior Software Engineer to join their Model Serving product team. This role focuses on designing and building scalable, low-latency inference systems for AI/ML models (traditional ML to LLMs) on CPU and GPU. Responsibilities include optimizing performance, throughput, autoscaling, and operational efficiency, as well as contributing to core serving infrastructure components like routing, caching, and observability. The role requires strong experience in large-scale distributed systems and model serving infrastructure.

Databricks is seeking a Staff Software Engineer to work on their Model Serving product, which is a core pillar of their platform for enterprises to deploy and manage AI/ML models. The role involves designing and building systems for high-throughput, low-latency inference across CPU and GPU workloads, influencing architectural direction, and collaborating with various teams to deliver a world-class serving platform.

Staff Backline Engineer role at Databricks focused on deep-dive troubleshooting, root cause analysis, and architectural optimization within the Databricks Data and AI ecosystem. The role involves developing automated workflows and AI-driven diagnostic tools to improve supportability and scale the organization. Requires expertise in either Data Engineering, Product Supportability, or the AI track (ML/GenAI systems, LLMs, agentic workflows).