Compute Platform Engineer, License Scheduling

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 understa

P-1428 At Databricks, we run the world's largest AI platform. We believe the next breakthroughs will come from models trained on domain-specific enterprise data, not from bigger general-purpose models alone. That's why we built AI Runtime , a serverless product that makes GPU training of any size feel simple, so companies can train their own models the way frontier labs do. Customers across industries already use it to train models on governed data, from automotive AI at Rivian to Merck's TEDDY foundation models for single-cell biology and drug discovery, all the way to agents like KARL from Databricks AI Research. It takes a lot of engineering to make that work, and we've written about it on our blog: how we keep GPUs reliable , make training fault-tolerant , and speed up fine-tuning with fused kernels and smart sequence packing. As a Senior Software Engineer, you'll work on the systems behind all of this, solving hard technical problems and helping shape how AI Runtime evolves. The impact you will have: Build core parts of AI Runtime and contribute to Databricks' technical direction in AI training infrastructure. Develop reliability and observability features for a fleet that keeps growing in scale and complexity. Improve AI Runtime's developer experience, so the largest training jobs feel as simple as a first experiment. Help prepare AI Runtime for new GPU generations and workload types. Take on hard multi-node training problems, from orchestration and GPU scheduling to data loading and checkpointing. Make training faster and cheaper by raising GPU efficiency across model architectures and hardware generations. Work with research, product, and customers on what we build next and own features from design through production. Champion engineering excellence, raise the bar, and help the engineers around you grow. What we look for: 5+ years in large-scale distributed systems, with experience in GPU training, high-performance computing, or ML systems. Experience traini

P-1930 At Databricks, we run the world's largest AI platform. We believe the next breakthroughs will come from models trained on domain-specific enterprise data, not from bigger general-purpose models alone. That's why we built AI Runtime , a serverless product that makes GPU training of any size feel simple, so companies can train their own models the way frontier labs do. Customers across industries already use it to train models on governed data, from automotive AI at Rivian to Merck's TEDDY foundation models for single-cell biology and drug discovery, all the way to agents like KARL from Databricks AI Research. It takes a lot of engineering to make that work, and we've written about it on our blog: how we keep GPUs reliable , make training fault-tolerant , and speed up fine-tuning with fused kernels and smart sequence packing. As a Staff Software Engineer, you'll work on the systems behind all of this, solving hard technical problems and shaping major parts of AI Runtime. The impact you will have: Drive major parts of AI Runtime's architecture and help shape Databricks' long-term technical direction in AI training infrastructure. Design the reliability and observability systems for a fleet that keeps growing in scale and complexity. Lead improvements to AI Runtime's developer experience, so the largest training jobs feel as simple as a first experiment. Help choose the technical bets that prepare AI Runtime for new GPU generations and workload types. Take on the hardest multi-node training problems yourself, from orchestration and GPU scheduling to data loading and checkpointing. Make training faster and cheaper by raising GPU efficiency across model architectures and hardware generations. Work with research, product, and customers to shape what we build next and lead projects across teams. Champion engineering excellence, raise the bar, and mentor the engineers around you. What we look for: 10+ years in large-scale distributed systems, with significant depth in

P-1533 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. We are seeking an experienced Sr. Staff Software Engineer with deep networking expertise to help shape the future of Databricks’ Networking Infrastructure . As one of the early members of the rapidly growing Bangalore site, you will play a critical role in defining the technical vision and architecture for next-generation network connectivity & observability services that will power & manage millions of VMs across multiple clouds . In this role, you will own and drive the design of large-scale connectivity platforms that form the backbone between Databricks’ control plane and compute plane . These platforms are foundational to improving the scalability, reliability, and efficiency of our compute infrastructure, while enabling more intelligent and cost-effective use of cloud resources. You will operate at an org-wide level , setting technical direction, leading complex cross-team initiatives, and mentoring senior engineers. You’ll work closely with product management, operations, and partner engineering teams to translate long-term business goals into durable, extensible networking systems . This role requires both hands-on technical leadership and the ability to influence architecture and execution across teams. This is a unique opportunity for a senior technical leader who enjoys working in ambiguou

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are seeking a Senior Software Developer to join the Elasticsearch Security team. In this role, you will contribute to the architecture and design of Elasticsearch's main features. These features include authentication, authorization, and tenant isolation. You will work with engineering and product leaders at Elastic. Your goal is to participate in providing high-performance security at all levels. This includes ensuring that our distributed data store has top-quality security at scale. What You Will Be Doing Contributing to core security initiatives from architecture to production, focusing on the delivery of new critical features. Participating in the technical design, planning, and execution for major security components inside the Elasticsearch core engine. Developing the foundational security models for features. Optimizing security performance at scale in distributed systems environments. Applying cryptographic solutions to address genuine customer use cases. Ensuring robust data isolation within shared infrastructure supporting disparate customers. Monitoring and applying the latest advancements and best practices in security. This includes authentication, identity management, cryptography, and data access management. Collaborating with peers across the company to embed security into new customer features from the outset

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are seeking a Senior Software Engineer to join the Elasticsearch Security team. In this role, you will contribute to the architecture and design of Elasticsearch's main features. These features include authentication, authorization, and tenant isolation. You will work with engineering and product leaders at Elastic. Your goal is to participate in providing high-performance security at all levels. This includes ensuring that our distributed data store has top-quality security at scale. What You Will Be Doing Contributing to core security initiatives from architecture to production, focusing on the delivery of new critical features. Participating in the technical design, planning, and execution for major security components inside the Elasticsearch core engine. Developing the foundational security models for features. Optimizing security performance at scale in distributed systems environments. Applying cryptographic solutions to address genuine customer use cases. Ensuring robust data isolation within shared infrastructure supporting disparate customers. Monitoring and applying the latest advancements and best practices in security. This includes authentication, identity management, cryptography, and data access management. Collaborating with peers across the company to embed security into new customer features from the ou