Senior Gpu Memory Architect in United States

We are looking for a Senior System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response. What you'll be doing: Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow) Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes Drive upstream contributions to OVN-Kubernetes and related open-source projects Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure Drive reliability through incident management, resource monitoring, and performance tuning<

NVIDIA is looking for an experienced software engineer with infrastructure experience to become a senior member of the Cloud Foundations Automation - Development Team. We build and manage the automation ecosystem supporting NVIDIA's GPU Cloud and NVIDIA SuperPod deployments. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us. If you're creative and autonomous, we want to hear from you! What you'll be doing: Developing software to enable efficient network design, deployment and day 2 management. Building product focused software solutions, used by internal and external customers. Helping us as we transform our workflows and organization into a centrally orchestrated configuration management framework, operating at scale across geographies. Owning and driving integrations with various service APIs such as Cloud Service Providers, to automate creation of environments and auto populate data sources in turn. Building on open source software, designing and implementing data structures and UI interfaces to automate processes from equipment purchase to device config generation to deployment to operations. Streamlining deployment mechanisms and life cycle operations Developing modern service architectures around streaming data and event pipelines. Working with infrastructure domain experts on true, zero touch deployment solutions and utilizing best of breed high performance computing management solutions. Be a proactive problem solver, looking out for new opportunities to improve our services and customer experience. Communicate readily with your peers across the organization, b

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. We are looking for a highly motivated senior software engineer for an exciting role in our communication libraries and network software team. The position will be part of a fast-paced crew that develops and maintains software for complex heterogeneous computing systems that power disruptive products in High Performance Computing and Deep Learning. What you will be doing: Design, implement and maintain highly-optimized communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters. Participating in and contributing to parallel programming interface specifications like MPI/OpenSHMEM. Design, implement and maintain system software that enables interactions among GPUs and interactions between GPUs and other system components. Creating proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware. What we need to see: M.S./Ph.D. degree in CS/CE or equivalent experience. 5&#43; years of relevant experience. Excellent C/C&#43;&#43; programming and debugging skills. Strong experience with Linux. Expert understanding of computer syst

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

We are now looking for a Senior Deep Learning Software Engineer, PyTorch. NVIDIA is hiring software engineers to design and build tools used by AI engineers across the world to design, develop, and deploy AI applications scalable across thousands of GPUs. This position will embed you in an ambitious and diverse team that influences all areas of NVIDIA's AI platform as well as directly contributes to PyTorch, a premiere deep learning framework. In this role you will work with multiple teams at NVIDIA across fields, as well as collaborate internationally with the PyTorch community to develop the best AI platform in the world. What you will be doing: Design and build PyTorch components that run efficiently on supercomputers with 1000s-100ks of GPUs. Collaborate with NVIDIA’s hardware and software teams to improve the overall GPU performance in PyTorch. Design, build and support production AI solutions used by enterprise customers and partners. Work with internal applied researchers to improve their AI tools. What we need to see: BS in Computer Science or Engineering (or equivalent experience). 3&#43; years professional experience in deep learning. Proficient with C&#43;&#43; programming. Strong understanding of systems software and interfaces. Demonstrated experience with Thread and Distributed Parallel Programming Demonstrated background developing large software projects. Strong verbal and written communication skills Ways to stand out from the crowd: Contributions and participation in the open source community. Familiarity with deep learning compilers. Familiarity with deep learning modeling trends. Background with CUDA Programming as well as Python.

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. We are a world - class autonomous driving hardware and software development team. We have the best platform and have maintained a leading position in the field of artificial intelligence. Next, we will continue to deepen our efforts in the autonomous driving field and strive to bring sustained growth to our customers. We're looking for a Senior Software Triage Engineer with strong technical ability to deeply understand architectures and strong scripting experience to automate and Triage methodology, and the leadership to encourage our engineering team. As a key member of our automotive group, you'll be working on the real time challenges outstanding to the automotive industry and our automotive products. This is a key role to support AV software agile iteration & development for the release of clients, together working with the engineering teams, understanding the AV stack deeply and providing data-based judgement and delivering high-quality AV software to end customer. What you’ll be doing: Work with Product, Engineering, Model/SW Devs, In-car testing, Fleet teams on test request and triage planning, do live triage with accurate analysis and debugging steps, present top issues by end of day. Deep understand

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. As a Formal Verification Engineer at NVIDIA, you will verify the build and implementation of the industry's leading GPUs. In this position, your responsibilities will be to verify the micro-architecture using formal verification tools, define the verification scope, and ensure correctness. You will employ sophisticated formal techniques to acquire sufficiently bounded proofs while working with architects, designers, and pre- & post-silicon verification teams to accomplish your tasks. You will efficiently complete the formal verification effort for the entire project cycle, delivering high-quality results on schedule, and clearly conveying those results to the team. What you will be doing: Identify key behaviors for verification to write clear testplans for sophisticated designs. Implement testplans using the latest formal techniques, including the development of environment assumptions, assertions, and cover properties. Develop abstraction models to overcome complexity challenges and acquire full proofs, or bounded proofs with sufficient coverage. Drive formal tools to realize their best performance. Debug RTL to identify causes of failure scenarios. Contribute to flow and script development

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 brain 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 a 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 Silicon Codesign Group is seeking a versatile engineer to join the HW bring-up methodology team. The SCG team is uniquely positioned to have an end-to-end view of the product development cycle - from early architecture definition, through bringup, to product release. What will you be doing: Led end-to-end planning and on-time execution of Nvidia's new chip bringup effort, from pre-silicon through production deployment. Coordinate multi-functional teams across Architecture, Build, Validation, DFT, SW, System, and Operations to drive shared bringup achievements. Improve cross-team communication, work, and handoffs. Develop and standardize methodologies, processes, and workflows for silicon bringup, creating reusable checklists and playbooks. Drive scheduling, equipment, and material logistics to support ambitious NPI and production schedules. Lead post-action reviews and convert learnings into concrete process improvements for future silicon and solution bringups. Contribute to post-silicon learnings that feed back into architecture, design, and pre-silicon

Build the infrastructure that keeps every NVIDIA chip aligned from first spec to final shipment. NVIDIA's Silicon Co-Design Group sits at the convergence of architecture, silicon, systems, and manufacturing. The System–Manufacturing Architecture (SMAC) team coordinates between system specifications and manufacturing test specifications from pre-silicon POR through production release across GPU, SoC, and CPU programs. When that alignment drifts, silicon faces the consequences: escapes, yield loss, and performance loss. We're hiring a Senior Manufacturing & System Co-Design Workflow Engineer to lead the methodology and infrastructure that maintains holistic, systematic alignment, at scale across the full portfolio. The strongest candidates in this role design the workflow before being asked to fix a program, and build the checks and automation that confirm alignment holds long after they've moved on to the next problem. What you’ll be doing: SMAC Workflow Methodology: Define manufacturing spec types, including schema and semantics, derived from system PORs and features. Own the methodology that governs how specification work gets structured, versioned, and validated across the program lifecycle. Production Python Pipelines & Automated Checks: Develop production-grade Python pipelines and automated checks that catch specification drift between system POR and manufacturing test programs ,ATE, SLT, BLT, L10&#43;, before silicon exposes the discrepancy. The goal is that misalignments surface in the workflow, not on the tester. E2E Program Integration & TPM Attestation: Wire SMAC work into the end-to-end program spine, milestones, gates, and artifacts, and define explicit TPM-driven attestation when checks lag. Alignment can't be assumed; it must be proven at every stage. Agent-Ready Tooling & CI Infrastructure: Integrate tooling into an agent-ready

Define the physical limits of what a chip can do, then break them! NVIDIA's Silicon Co-Design Group sits at the crossroads of architecture, silicon, systems, and manufacturing, where first principles thinking translates directly into product outcomes at scale. As GPU power density and thermal limits approach physical boundaries, the gap between system architecture needs and manufacturable, testable capabilities widens with every generation, and this role exists to close it. You wouldn't be maintaining existing solutions, you'd be identifying where physical constraints will erode NVIDIA's competitive edge before anyone else sees it coming, then building the cross-domain responses that ensure the next generation leapfrogs those limits entirely. The problems here don't have known answers yet: Every generation of NVIDIA silicon pushes closer to the limits of physics. The Co-Design Architect role isn't about optimizing within known bounds; it's about redrawing those bounds entirely. If you want your work to shape what's physically possible in the world's most demanding computing products, this is where that work happens. What you'll be doing: Power, Thermal & Packaging Limits Analysis: Gather and analyze the hard constraints of packaging, power delivery, and thermal dissipation against roadmap demands, predicting when those constraints will reduce competitiveness and acting before they do. Cross-Domain Solution Development: Develop solutions that span silicon features, packaging innovation, firmware and hardware co-design, and DFX updates, ensuring future products are not only performant but testable to the highest quality and reliability standards. Packaging Technology Evaluation: Assess emerging packaging technologies for their voltage/frequency, noise, reliability, and testability implications, determining which are worth adopting 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 a 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. Silicon Co-Design Group (SCG) is a wide-ranging, multi-functional, integral team at NVIDIA. We sit at the crossroads of design, architecture, marketing, operations, and productization. Our contributions span from the arch stage and extend to defining final products. We architect innovative solutions for Datacenter, Server, Gaming, Robotics, Automotive, and Embedded markets. We are fast-paced, dynamic, share a sense of humor, and collaborate extensively to push the boundaries of what is possible. We do all of this with an eye on making groundbreaking, impactful market disruptions! We are seeking an experienced Senior Manager to lead Product Co-Design and Verification in areas of Speed, Reliability and Power Compliance. You will oversee speed/timing/reliability system design, Simulation-to-Silicon power/speed verification, features for product compliance and test chip development crating future product roadmaps. The ideal candidate will have deep technical expertise in semiconductor/VLSI design and a background in translating product requirements into design and vice versa. This is a highly visible, multi-functional role to produce outstanding products that ship at SOL and meet the high NVIDIA quality we demand and customers expect. <p

Are you ready to contribute to world-class innovation and push the boundaries of what's possible? At NVIDIA, you'll have the opportunity to be part of a team that is driving groundbreaking impacts across various markets. As a Thermal Solutions Development Engineer, you will play a pivotal role in our Silicon Codesign Group, transforming thermal solution concepts into lab-ready builds and beyond. What you will be doing: Build thermal solutions for engineering characterization and validation of next-gen GPU/SOC products, ensuring flawless delivery from concept to lab. Drive end-to-end development and deployment of thermal solutions, collaborating with internal teams and external vendors on build requirements, prototype evaluation, test system integration, and software automation. Improve thermal design processes by incorporating feedback and findings, developing workflow and maintaining our world-class standards. Work closely with system architects, chip and board designers, and software/firmware engineers in a dynamic and high-energy environment to bring industry-defining products to market. Apply AI-enabled approaches and AI tools to accelerate design iteration, test planning, and characterization/validation triage (e.g., requirements/spec summarization, experiment prioritization, log/telemetry summarization, anomaly/outlier detection), improving cycle time, coverage, and traceability while validating outputs against physics, specs, and lab measurements. Partner with AI/tooling teams as the thermal domain SME to define use-cases, success criteria, and evaluation methods; provide feedback to improve tool reliability and usability. What we need to see:

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. At NVIDIA, we are seeking a Senior Account Manager who will bring technical and business insight to help grow the Networking business with Cloud Service Providers, leveraging NVIDIA’s fast-growing Datacenter Networking Business. What you'll be doing: You will be an integral part of a small, forward-thinking team responsible for a significant and rapidly growing revenue contribution to the Enterprise products group, the fastest growing and most dynamic segment at NVIDIA. Working with leading CSP to grow deployment of NVIDIA networking solutions Define and drive the discussions, strategy and tactics for achieving revenue growth Partner and collaborate with technical teams on roadmap updates, new designs, competition Representing the customer’s strategy & needs to internal stakeholders and vice versa Delivering a concise state of the business at any given time What we need to see: Bachelor’s degree or higher in related field (or equivalent experience). 12&#43; years of Technical Sales or Product Management with focus on Data Center Networking for CSPs An understanding of the business and technology landscape of CSP Data Center Networking <l

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 is seeking best-in-class ASIC Verification Engineers to verify the design and implementation of the world’s leading inference accelerator. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of outstanding people around the globe. Their mission is to push the frontiers of what is possible today and define the platform for the future of computing. In this position, you will help to build the high-performance processor elements that implement programmable compute and graphics functionality. What you'll be doing: As a key member of our ASIC Verification team, you will verify the design and implementation of inference accelerator You will be responsible for verification of the ASIC design, architecture, reference models and micro-architecture using advanced verification methodologies Understand the design and implementation of your unit, define the verification scope, develop the verification infrastructure and verify the correctness of the design Collaborate with architects, designers, and pre and post silicon verifi