Nvidia Manager Jobs

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 seeking a Staff DB SRE to build the runtime foundation for NVIDIA’s enterprise AI platforms — with a strong emphasis on database infrastructure at scale. This role blends large-scale database transformation with the building and development of GPU-accelerated platforms. You'll develop the software systems, automation frameworks, and high-performance database services that power NVIDIA’s AI workloads at scale. What you'll be doing: Design and operate highly available database clusters (MySQL, MSSQL, Oracle) with automated replication, failover, point-in-time recovery, and disaster-recovery strategies at enterprise scale. Drive database performance engineering — own query optimization, indexing strategies, connection pooling, lock-contention analysis, and storage-engine tuning for production systems handling millions of transactions. Build self-service database lifecycle automation — from one-click cluster provisioning and schema migrations to zero-downtime upgrades, blue-green deployments, and automated capacity scaling. Bridge relational and AI-native data infrastructure — extend traditional database exper

We are now looking for a Senior SRAM Engineer within our Full Custom Memory (FCM) team! The FCM team designs specialized RAM implementations across NVIDIAs wide array of processing chips. Be it high speed, low power, multiport, we engage closely with processor architecture teams to build custom solutions across the entire NVIDIA silicon portfolio. Are you interested in designing circuits for the next generation of AI chips? Join a team of dedicated engineers developing the custom SRAM circuits that help power these chips. What you'll be doing: Design best-in-class SRAM circuits using state-of-the-art technology processes Optimize circuits for performance, area, and power Collaborate with mask designers to craft high quality and dense pitch-matched layout Verify functionality, electrical integrity, and robustness Improve/develop flows and methodologies to streamline design automation, data collection, and analysis to ensure working silicon What we need to see: BS/MS/PhD (or equivalent experience) in Electrical or Computer Engineering Minimum 12 years of circuit design experience Strong understanding of SRAM and memory design techniques and macro/block development Ways to stand out from the crowd: Self-motivation, attention to detail, clear data analysis and presentation skills Familiarity with industry tools such as Cadence Virtuoso for schematic and layout, SPICE simulators, waveform viewers Background with developing and using various flows and methodologies, in

NVIDIA is the world leader in GPU Computing. We are passionate about markets including gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you. We are now looking for a Software QA Test Development Engineer, you will collaborate with multi-functional groups. SWQA test developer engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA engineer can improve productivity or optimize test plan. As a SWQA test developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What You’ll Be Doing Analyze requirements and design test matrices covering functionality, performance, and edge cases. Develop test plans and cases; build and maintain automated test suites (API / UI / CLI / E2E) in Python. Leverage AI-powered tools and agentic workflows to accelerate test generation, triage, and root cause analysis. Manage the full bug lifecycle — filing, reproduction, and driving multi-functional collaboration to resolution. Reproduce and verify customer-reported issues to ensure quality before release.

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. What you’ll be doing: Use and develop AI-powered tools to make software testing smarter, faster, and more effective! Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization. Work with product, engineering, and cross-functional teams to review requirements and define test strategies. Build test plans, design and execute test cases, and report quality status, risks, bugs, and results. Perform functional, performance, fault-injection, reliability, and regression testing for cloud-native systems. Automate test cases and contribute to scalable test frameworks. Manage the bug lifecycle, reproduce customer issues, and verify fixes. What we need to see: MS or PhD in Computer Science, Engineering, or a related field. 5+ years of QA, test automation, or software testing experience. Hands-on experience using AI tools to improve QA workflows. Strong QA fundamentals, test strategy, test planning, and failure analysis skills. Proficiency with Unix/Linux and shell or Python programming. Exp

We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team. What you’ll be doing: Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc. Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities. Drive joint architecture reviews and “whiteboard” sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests. Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites. Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins). Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters. Proven track record debugging large-scale, cloud-native stacks across ne

We are now looking for an AI Developer Technology Engineer Interns. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time — the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human creativity and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Come join a team full of world-class computer scientists to work in its Compute Developer Technology team as an AI Developer Technology Engineer. What you will be doing: Work and develop state of the art techniques in LLM/AIGX/GR, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures You will provide the best AI solutions using GPUs working directly with key customers Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and

We are now looking for a Senior Chip Design RTL Design Engineer for the Switch Silicon group. As a Chip Design Engineer at NVIDIA's Networking business unit, you'll join a group of passionate engineers to design and implement the next generation state of the art Switch Silicon chips. In this position, you'll make a real impact in a dynamic, technology-focused company while developing the industry's best high-speed communication devices, delivering the highest throughput and lowest latency! What you'll be doing: Work in a combined design and verification team which develops some of the switch silicon core units. Plan and Design RTL units / blocks according to Arch & Micro arch specifications under challenging constraints with high orientation to power, area, and performance. Build reference models, verify and simulate chip blocks/entities according to specifications. Work closely with multiple teams within organizations such as Architecture, Micro- Architecture, and FW. What we need to see: B.Sc. in Electrical Engineering or Computer Engineering. 4&#43; years of experience in RTL design or RTL verification. Previous experience in networking - an advantage. A team player with good communication and interpersonal skills. NVIDIA has some of the most forward-thinking and hardworking people in the world working for us. Are you creative and autonomous? Do you love the challenge of crafting the highest performance & lowest power silicon possible? If so, we want to hear from you. Come, join our Switch Silicon design team and help us build the next chip in this exciting and quickly growing field. #LI-Hybrid <

NVIDIA is looking for an excellent Senior Firmware Verification Engineer for NVIDIA FW PHY verification Group. The person will be part of FW PHY verification of NVIDIA Products. Will closely work with NVIDIA FW PHY development, architecture teams and gain deep understanding of NVIDIA's products and technologies. What you'll be doing: Own the responsibility for delivering Networking features and their verification aspects. Define, develop and maintain verification infrastructure and regression tests suites - make test suites robust, maintainable and easy portable. Work with continuous integration system, regression tools, automate builds, run test suites and analyzing results. Innovate! Bring NVIDIA product to next quality level What we need to see: B.Sc. in Computer Science / Computer Engineering / Electrical Engineering / Communication Engineering 5&#43; year of relevant experience working with established brands Experience with Verification and Automation Programming Knowledge in C and C &#43;&#43;, object-oriented OOP Knowledge in Linux Creative, motivated and value-driven person Ways to stand out from the crowd: Background with C/C&#43;&#43; as well as Git Experience with python Experience with Networking applications and protocols Background with CI methodology & tools (Gerrit, Jenkins etc.) NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous engineer who loves a challenge? Are you ready to become the engineer you always wanted to be? Come and be part of the best chip design team

NVIDIA is leading 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 groundbreaking creativity and discovery, and powers inventions that were once considered science fiction, including artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We build communication libraries like NCCL, NVSHMEM, and UCX that are crucial for scaling Deep Learning and HPC. We're seeking a Senior Software Architect to help co-design next-gen data center platforms and scalable communications software. DL and HPC applications have a huge compute demands and already run at scales of up to tens of thousands of GPUs. GPUs are connected with high-speed interconnects (e.g. NVLink, PCIe) within a node and with high-speed networking (e.g. InfiniBand, Ethernet) across nodes. Efficient and fast communication between GPUs directly impacts end-to-end application performance. This impact continues to grow with the increasing scale of next generation systems. This is an outstanding opportunity to advance the state-of-the-art, break performance barriers, and deliver platforms the world has never seen before. Are you ready to build the new and innovative technologies that will help realize NVIDIA's vision? What you will be doing: Investigate opportunities to improve communication performance by identifying bottlenecks in today's systems. Design and implement new communication technologies to accelerate AI and HPC workloads. Explore innovative solutions in HW and SW for our next generation platforms as part of co-design efforts involving GPU, Networking, and SW architects. Build proofs-of-concept, conduct experiments,

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 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 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

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 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 the GPU Communications Libraries and Networking team at NVIDIA. We deliver libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available Triage and root-cause performance issues reported by our customers Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information <li

Deep Learning Software Engineering Intern, Test Development - 2027 — Shanghai, China. Apply via Workday.