Cluster Hr Head in United States

At NVIDIA, we push the boundaries of computing innovation. Our ASIC Verification Engineers focus on developing the world’s top SoCs and GPUs. Joining us as a Senior ASIC Verification Engineer - GPU means working on modern technology powering consumer graphics and AI applications. This position is ideal for those passionate about technology and eager to impact computing’s future. What you'll be doing: As a key member of our ASIC Verification team, you will verify the design and implementation of the industry's leading GPUs. You will be responsible for verifying the ASIC build, architecture, golden models, and micro-architecture using advanced verification methodologies such as UVM or equivalent. Understand the design and implementation of your unit/cluster/chip, define the verification scope, develop the verification infrastructure, and verify the correctness of the design. Collaborate with architects, designers, and pre- and post-silicon verification teams to accomplish your task. What we need to see: Bachelor's Degree in EE, CS, or CE or equivalent experience. 5+ years of relevant experience. Experience in verification using random stimulus along with functional coverage and assertion-based verification methodologies. Experience with design and verification tools (VCS or equivalent simulation tools, debug tools like Verdi, Indago, GDB). Expertise in System Verilog or similar HVL. Strong debugging and analytical skills. Perl and C/C++ programming language experience desirable. Strong communication skills and the ability & desire to work as a great teammate are huge pluses. Experience in crafting test bench environments for unit and system level verification. #LI-Hybrid Your base salary will be det

NVIDIA is hiring an NCX Senior Engineer who is passionate about NVIDIA Cloud Partner (NCP) infrastructure operations to join our DSX team. This role involves working closely with strategic NVIDIA Cloud Partners to build and improve the operational capabilities essential for running large-scale NVIDIA accelerated infrastructure reliably in production. Your role involves guiding partners beyond the initial cluster deployment and validation phase into advanced Day 2 operations. These operations cover ongoing infrastructure health, observability, lifecycle management, quick remediation, performance validation, and operational readiness. You will engage directly with partner engineering and operations teams to develop consistent approaches that support NVIDIA workloads and the broader external customer environments of the partners. This is a highly technical, hands-on role at the intersection of NVIDIA accelerated computing, cloud infrastructure, distributed systems, and production operations. What you'll be doing: Lead NCP Day 2 operational readiness efforts. Collaborate directly with NVIDIA Cloud Partners to set up the systems, procedures, automation, and operational methods necessary to consistently manage NVIDIA accelerated infrastructure following initial deployment and activation. Build continuous infrastructure validation. Develop and implement methods to continuously validate GPU, CPU, storage, and network health. Do this across large-scale AI clusters to identify degraded infrastructure before it impacts critical training or inference workloads. Establish observability and operational telemetry. Help NCPs implement comprehensive telemetry, monitoring, alerting, dashboards, and operational signals across compute, GPU, InfiniBand/RoCE networking, storage, Kubernetes, and AI workloads. Devel

The opportunity Datadog’s Infrastructure products help engineers understand and operate the systems their applications depend on. Our customers work in complex environments like Kubernetes and serverless, where infrastructure changes constantly, information is dense, and decisions about reliability, performance, and cost are closely connected. We’re looking for a Staff Product Designer to join Modern Compute, with an initial focus on Containers Autoscaling. Autoscaling helps engineering teams make better decisions about how their applications and infrastructure use resources. Designing these experiences requires making deeply technical systems understandable, helping customers act with confidence, and fitting into the tools and workflows they already use. The team is rethinking how workload and cluster autoscaling come together as a more coherent product experience. This includes how customers get started, understand recommendations, evaluate value, and safely apply changes across their environments. The work also connects to other parts of Datadog, including observability, Cloud Cost Management, permissions, and AI-assisted workflows. As a Staff Product Designer, you will help define that direction and lead the work from early problem framing through shipped product. You will partner closely with product and engineering, bring a high level of interaction and visual craft to complex workflows, and help raise the quality of design across Modern Compute. At Datadog, we place value in our office culture, the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to help our Datadogs find a work-life rhythm that works for them. What you’ll do Lead end-to-end product design for Modern Compute, initially focused on our Autoscaling product. Help define the product direction for an area that is still evolving, from early framing and exploration through detailed design and delivery. Design clear, trustwort

About the Team This team builds and operates the systems that enable OpenAI researchers to run reliable, scalable, and efficient research workflows. The team sits close to research and works across infrastructure, systems, and automation to make sure researchers have the tools and environments they need to move quickly. The work spans software engineering, infrastructure, systems administration, cluster operations, and reliability engineering. As OpenAI’s infrastructure evolves from bespoke bare-metal systems toward more standard, scalable platforms, the team needs engineers who can understand how systems work end-to-end and build the right abstractions without reinventing the wheel. About the Role As a Software Engineer on this team, you will build and operate the infrastructure that supports frontier research and critical research-facing systems. You will work on systems that sit close to the metal, but the role is not limited to classic operations or sysadmin work. We are looking for someone who can reason about networking, bootstrapping, Kubernetes, scalability, automation, and reliability - while also writing software to make these systems better over time. This role is a strong fit for an independent, high-ownership engineer who enjoys reliability-heavy infrastructure work but still wants to build. You do not need to come in as a kernel expert or highly algorithmic optimization engineer, but you should be deeply curious about infrastructure, comfortable debugging complex systems, and excited to support researchers doing novel work. We expect you to: Build and operate reliable infrastructure for research workloads and research-facing services. Support and improve systems across data infrastructure, processing, crawl and ingest, caching, search, observability, and clusterwide services. Improve cluster bootstrapping, provisioning, automation, and deployment workflows. Debug issues across networking, compute, storage, orchestration, and service reliability layers.

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

About the Team OpenAI’s Infrastructure organization builds the systems that power frontier AI workloads at global scale. As compute demand accelerates, our ability to rapidly convert infrastructure investments into usable production capacity has become mission critical. The CPU / Storage / PoP / WAN team is responsible for the end-to-end infrastructure layers required to bring compute online: server and cluster activation, storage platforms, Points of Presence (PoPs), backbone connectivity, and global network expansion. We operate across first-party facilities, colocation environments, and strategic cloud partners to ensure OpenAI can scale reliably and quickly. About the Role We are seeking a highly technical Program Manager to lead execution across CPU, Storage, PoP, and WAN infrastructure programs that directly unlock OpenAI’s next generation compute capacity. In this role, you will own complex cross-functional programs spanning compute cluster activation, storage deployment, PoP bring-up, and backbone expansion. You will coordinate hardware readiness, site readiness, network pathing, storage availability, vendor execution, and engineering dependencies required to turn contracted infrastructure into live training and inference capacity. This role requires strong technical fluency across hardware systems, network infrastructure, storage architecture, and deployment execution. You should be comfortable operating from rack-level implementation details through executive-level capacity planning discussions. This role is based in San Francisco, CA, with travel as needed. Key Responsibilities Lead end-to-end execution of CPU / GPU cluster activation programs across OpenAI’s global infrastructure footprint Drive readiness to convert contracted compute capacity into schedulable production clusters Own deployment programs for new PoPs, backbone nodes, WAN expansion, and interconnection initiatives Build integrated schedules spanning procurement, logistics, installation, st

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. NVIDIA GH200 superchip provides performance and productivity required for strong scaling for HPC and generative AI workload. Scale out is inherent to design of this massive superchip. We are looking for expert engineers to come and help design rack level solutions for next generation scaling AI supercomputing platforms. We are looking for a strong technical architect to own end to end manageability architecture for these products in data centers. You will work with various component leads internally and externally, drive customer use cases, align architecture with customer requirements and release best products to market. Join us at the forefront of technological advancement. What you’ll be doing: Drive server management for large clusters and data centers deploying GPUs and Grace solution from Nvidia. Work with data center architects and cloud customers to narrow down on requirements for implementation to ensure speed of light product development. Work with internal teams to make sure requirements are designed and implemented in right way with each firmware and software module Collaborate with other leads to design & build data center health management workflow. Drive reliability and optimization in firmware architecture from a data center view point. Work closely with cluster bring up team and resolve is

NVIDIA is looking for a hands-on Solutions Architect Manager to lead a team of GPU, networking & software solution architects and engineers. Do you want to build and lead a group that designs, debugs, and deploys new AI hardware and software technologies into production in customer data centers? As part of the NVIDIA SA organization, you will drive people and technical leadership for end-to-end solutions deployments at some of NVIDIA's most strategic technology customers, while directly contributing to designs and deep-dive debugging and shaping our product roadmap with customer feedback. What you will be doing: Recruit & manage a team of solutions architects, system/network and software engineers focused on large-scale GPU and AI networking deployments. Set priorities, allocate resources, mentor, and ensure high-quality customer delivery across multiple concurrent projects - while remaining directly involved in key technical reviews, design decisions, and critical debug efforts. Provide deep subject-matter expertise in advanced GPU and network systems and serve as the senior technical point of contact for strategic customers. Personally lead and guide complex compute/network configuration and performance debugging, working side-by-side with your team to deliver performant, reliable clusters. Guide your team as they lead network / compute / software architecture discussions, and support server, network, and cluster bring-up, including on-site data center work where needed. Systematically collect and synthesize customer-specific requirements across your portfolio. Partner with GPU/Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and packaging of reference designs and solutions. Demonstrate SME in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers. Bring customer-sp

Cloud Platform Administrator (Mid-Level, Senior or Lead) **Sign on Bonus Potential** Company: The Boeing Company The Boeing Company’s Specialized United States Infrastructure Operations is currently seeking a Cloud Platform Administrator (Mid-Level, Senior or Lead) to join the team in Berkeley, MO; Seattle, WA; or Daytona Beach, FL . The Infrastructure team is seeking a skilled platform engineer to help build and operate the cloud platform services that host critical enterprise applications and software toolchains. In this role, the selected candidate will focus on the shared platform capabilities that enable teams to deploy, run, and maintain containerized and cloud-hosted solutions in a consistent and supportable manner. As both an individual contributor and technical leader, this position will help define and implement platform standards for Kubernetes, container hosting, deployment automation, configuration management, and operational support. This role is focused on platform reliability, repeatability, scalability, and service enablement, rather than custom application software development. Position Responsibilities: Design, implement, and maintain cloud platform services supporting Kubernetes, containers, ingress, storage integration, secrets management, and service connectivity Build and sustain reusable deployment patterns for Commercial-Off-The-Shelf (COTS), Open Source Software (OSS), and internally customized applications Develop and maintain automation for platform provisioning, upgrades, patching, and lifecycle support Manage cluster lifecycle activities including: Cluster upgrades Node management <

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As an OS / K8s Systems Engineer at Baseten, you’ll build the automation and systems that turn raw GPU hardware into production-ready compute. From provisioning to orchestration, you’ll own the software layer that makes our infrastructure reproducible, scalable, and reliable across data centers. This is a senior, hands-on role focused on building systems not operating them. You’ll work close to the metal designing OS images, building provisioning pipelines, and automating cluster bring-up from scratch. Your work will define how quickly we can turn new capacity into usable compute. EXAMPLE INITIATIVES Zero-to-cluster automation Build workflows that take new hardware from unprovisioned to fully operational cluster. Provisioning systems Design PXE-based or equivalent systems for imaging and lifecycle management. Reproducible infrastructure — Ensure clusters deploy consistently across data centers. RESPONSIBILITIES Own the end-to-end automation of cluster bring-up and lifecycle management. Build and maintain OS images, provisioning systems, and configuration pipelines. Deploy and operate cluster orchestration platforms (Kubernetes, Slurm, or similar). Design systems for reproducibility across sites and hardware generations. Automate upgrades, rollouts, and failure recovery. Optimize system performance, including GPU utilization and networking. Partner with hardware and network teams to validate and improve system b

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE At Baseten, we’re looking for a Technical Program Manager to drive our most complex, cross-cutting infrastructure programs. This role will operate across all domains of AI infrastructure, from the GPUs up to the multi-cluster orchestration layer. This is an execution-first role. The work is less about owning a single system and more about imposing order on ambiguity: standing up the right structures, driving decisions to closure, and making sure nothing falls through the cracks across dozens of stakeholders. If you take satisfaction in turning a chaotic, half-defined initiative into a predictable, well-governed program, this role is for you. RESPONSIBILITIES Own complex migrations end to end. Lead large-scale infrastructure migrations across teams and domains. This will involve scoping the work, sequencing dependencies, managing risk, and driving them to completion without surprises. Drive process across infrastructure. Establish and run the operating rhythms that keep programs healthy: planning cadences, status reporting, decision logs, risk reviews, and escalation paths. Make the process light enough that teams adopt it and rigorous enough that it actually works. Help managers build the right structures. Partner with engineering managers and leads to design the team structures, ownership boundaries, and working models a program needs to succeed. Spot gaps in accountability before they become problems. Own fo

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Principal Software Engineer leading Fleet Management, you will be the overall technical lead across three pods and the person who sets the technical direction for the fleet management layer of Roblox. This is a hands-on, deeply technical leadership role that owns all of Roblox's compute capacity end to end: from low-level provisioning and the data plane, up through the control planes that operate it, and all the way to the UI and internal-facing products that let teams self-serve capacity. Your org centralizes security, maintenance operations, and the uptime of every Roblox Kubernetes cluster, and governs the internal customer contracts that drive automation across the fleet spanning Roblox data centers and cloud providers. You will guide architecture, raise the engineering bar, and make sure compute capacity supply and demand stay in balance as the fleet grows. You will: Serve as the overall technical lead for three Fleet Management pods, setting and aligning the technical direction across low-level provisioning, the data plane, and the control plane and product surfaces above them. Architect the declarative, Kubernetes-style control planes that operate Roblox's compute fleet across o