Hpc Dev Ops Engineer Jobs

About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal t

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 ship AI products. ABOUT THE ROLE This role owns Baseten's relationships and market intelligence across the hardware and chip layer of the compute stack: NVIDIA directly and key OEM partners such as Dell, Lenovo, Pegatron, and Supermicro. As Baseten's compute strategy increasingly depends on hardware access and terms, this role is central to keeping Baseten ahead of the market. WHAT YOU'LL DO Build and maintain relationships across NVIDIA and key OEM partners (e.g. Dell, Supermicro) Track market intelligence on hardware availability, roadmaps, and terms to keep Baseten informed and strategically well-positioned Support deal structuring and negotiation in partnership with Baseten's deal-making function Work closely with Infrastructure and Hardware Platform engineering teams to ensure consistent, high-quality provider relationships and engineering partnerships Represent Baseten credibly across senior relationships in the hardware ecosystem, escalating to company leadership when strategically valuable WHAT WE'RE LOOKING FOR Existing relationships and credibility within the NVIDIA, OEM, and HPC ecosystem Strong relationship-management instincts, with the judgment to know when to bring in senior leadership for maximum impact Comfort operating in a fast-moving, high-stakes market where hardware access can be a major competitive differentiator Collaborative style — this role depends on close coordination with engineering counterparts, not just ex

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Sr Design Engineer, you will work on design, simulation, and validation of next ‑ generation High ‑ Bandwidth Memory (HBM) architectures and circuit blocks. HBM requires advanced DRAM design knowledge combined with deep understanding of 3D stacked architecture, TSV signaling, wide I/O interfaces, PHY timing, power integrity, and system co ‑ optimization with GPUs/accelerators. This role sits at the intersection of DRAM design and high ‑ performance computing, enabling future AI/ML, HPC, and advanced graphics products. In this position, you will collaborate with Micron’s various design and verification teams all over the world and support the efforts of groups such as Product Engineering, Test, Probe, Process Integration, Assembly and Marketing to proactively design products that optimize all manufacturing functions and assure the best cost, quality, reliability, time-to-market, and customer satisfaction.

NVIDIA is seeking a Senior Firmware Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware development with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you will be doing: Design and develop firmware solutions for manageability and observability of data center servers. Actively participate in hardware bring-up activities, OOB firmware development, protocol stacks (Redfish, PLDM, MCTP, NSM) and hardware-software co-design for Cloud Service Provider deployments. Debug and troubleshoot NVIDIA GPU firmware issues, power management, performance, and thermal control problems for data center deployments, providing active support to CSPs. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Deep expertise in embedded firmware, server management controllers, and hardware bring-up with proven track record of shipping production BMC solutions Strong knowledge of DMTF protocols (Redfish, IPMI, PLDM, MCTP, SPDM), telemetry frameworks, and out-of-band management architectures Expert-level skills in C/C&

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We're searching for a highly technical, motivated manager to lead & manage the team responsible for rack-scale system software architecture. From firmware, kernel drivers, operating systems, networking, fabrics and associated user mode drivers + manageability software. You will work with component leads internally and engage with industry leading hyperscalar / cloud service providers on taking these products to market. What you’ll be doing: Drive the software end-to-end architecture for NVIDIA's rack-scale products Maintain deep understanding of the product portfolio and roadmap; translate forward-looking plans into clear, formal software requirements that anchor execution across the organization. Ensure high quality & reliable

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each brings together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We are searching for a highly motivated engineer to lead performance benchmarking and optimization efforts for our data center products. You will be instrumental in ensuring our data center solutions deliver industry-leading performance for accelerated computing workloads. What you will be doing: Design and execute comprehensive performance benchmarking strategies for our data center platforms and products Characterize real-world AI training, inference, and HPC workloads at scale Define, track, and report key performance indicators (throughput, latency, efficiency, scaling) Build automation tools and frameworks for performance monitoring and analysis Identify and analyze performance bottlenecks across compute, memory, network and storage subsystems Work closely with architecture, hardware,

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We’re searching for a highly motivated, technical leader to design, drive, and operationalize rack-scale factory and deployment flows for next-generation data center products. The ideal candidate will combine deep systems expertise, decisive technical leadership, and a passion for building reliable, debuggable, and scalable manufacturing and deployment solutions. What you’ll be doing: Lead and drive rack-scale/L11 flows for factory and initial data center deployment. Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations. Collaborate with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp. Champion reliability, debuggability an

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We're searching for a highly motivated, technical leader to drive the engineering roadmap and innovation for our rack system software architecture. From firmware, kernel drivers, operating systems, networking, fabrics and associated user mode drivers + manageability software. You will work with component leads internally and engage with industry leading hyperscalar / cloud service providers on taking these products to market. What you’ll be doing: Drive the software end-to-end architecture for NVIDIA's rack-scale products Maintain deep understanding of the product portfolio and roadmap; translate forward-looking plans into clear, formal software requirements that anchor execution across the organization. Ensure high quality & reliable software; serving as a trusted architectural partner to teams requiring

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The AI Cluster Production Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of large-scale multi-GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared, not monetized. Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization. The Opportunity CZ Biohub's mission is to cure or prevent all human disease. Achieving that requires training frontier-scale AI biology models, and that demands reliable, high-performance compute infrastructure. This is production engineering work at a frontier AI lab, with the twist that the mission is biology and the science is open. You'll keep GPU clusters running at high utilization, debug the toughest distributed systems failures, and build the operational foundations for scaling to multi-thousand GPU hero runs. The technical problems are genuinely hard (e.g., multi-node distributed training, InfiniBand fabrics, large-scale storage, Slurm at scale) inside an organization where the work is aimed at helping peop

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! We’re looking for a senior engineer to help build, maintain and evolve the training framework that powers our frontier-scale language models. This role sits at the intersection of large-scale training, distributed systems, and HPC infrastructure. You will design and maintain the core components that enable fast, reliable, and scalable model training — and build the tooling that connects research ideas to thousands of GPUs. If you enjoy working across the full stack of ML systems, this role gives you the opportunity and autonomy to have massive impact. What You’ll Work On Build and own the training framework responsible for large-scale LLM training. Design distributed training abstractions (data/tensor/pipeline parallelism, FSDP/ZeRO strategies, memory management, checkpointing). Improve training throughput and stability on multi-node clusters (e.g., GB200/300, AMD, H200/100). Develop and maintain tooling for monitoring, logging, debugging, and developer ergonomics. Collaborate closely with infra teams to ensure our cluster, container environments, and hardware configurations support high-performance training. Investigate and res

Datadog's integrations are the connective tissue between our platform and the technologies our customers run in the real world. As a Sr. PM on the Agent Integrations team, you will own the vision, prioritization, and execution for 100+ integrations that run directly inside the Datadog Agent from foundational infrastructure (MySQL, Kafka, Kubernetes) to the rapidly growing landscape of self-hosted AI and on-premise enterprise technologies. This is a high-impact, breadth-first role at the intersection of infrastructure observability and the frontier of AI-native workloads. At Datadog, we place value in our office culture; the relationships it builds, the creativity it brings, and the collaboration of being together. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Own the Agent Integrations roadmap. Determine which new integrations to build and which existing ones to improve, balancing customer demand, business impact, and engineering capacity across a catalog of 100+ technologies. Drive the expanding AI integration surface. Lead product strategy for self-hosted AI workloads, including LLM inference frameworks (e.g., Hugging Face TGI, BentoML), AI agents, MCP servers, and model orchestration tools, so Datadog customers can monitor every layer of their AI stack. Expand on-prem and hybrid coverage. Prioritize and execute new integrations for on-prem technologies including storage systems, HPC schedulers, network devices, and legacy enterprise platforms where customers run critical workloads. Build observability for ERP systems. Define and drive Datadog's strategy for monitoring enterprise ERP platforms (SAP, Oracle EBS/Fusion, Microsoft Dynamics) covering performance, job execution health, and integration layer telemetry so enterprise customers can observe their ERP stack alongside the rest of their infrastructure. Analyze adoption and customer feedback at scale. Use data from multiple sources to

About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need