Nvidia Jobs

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&

We are looking for a Senior Software Engineer to become part of our storage management plane team. The management plane is a web-based application crafted to provide our storage customers the capabilities to handle and supervise our distributed storage infrastructure. Our team is continually dedicated to acquiring and implementing ground breaking technologies to overcome obstacles and innovate solutions for improving our ability to handle large clusters of machines efficiently. What You Will Be Doing: Maintain and develop Kubernetes operators and our Container Storage Interface (CSI) plugin. Develop a web-based solution that manages, operates and monitors our distributed storage. Work closely with other teams to define and implement new APIs. What We Need to See: B.Sc., M.Sc. or Ph.D. in Computer Science, or related discipline, or equivalent experience. 8+ years of experience in web development ( both client and server ) Proven experience with Kubernetes (K8s), including developing or maintaining operators and/or CSI plugins. Experience scripting with Python, Bash or similar. Experience with nodejs is a must At least 5 years of experience working in a Linux OS environment You’re smart and a quick learner You do what it takes to get the job done Passionate about coding and big challenges Ways to stand out from the crowd: NodeJS for the server side: dominant modules are async & express . Kafka, MongoDB, K8s JavaScript frameworks: React, jQuery, c3j

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

By submitting your resume, you’re expressing interest in our 2027 RDSS (Research and Development Substitute Services) program. Please confirm your eligibility with the local district office before applying the role. 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 AI — 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 are looking to grow our company, and grow our teams with the smartest people in the world. What you’ll be doing: You will work with ground breaking technologies for the Tegra SoC and various NVIDIA embedded platforms Implement power and thermal management software features in Linux Kernel and user space Collaborate with power architects, hardware and software engineers on usecase power estimation, power and performance optimization What we need to see: MS in CS, CE, EE, Systems Engineering or related software/hardware engineering major Software development experience with a significant focus on Linux Excellent C programming/debugging skills within Linux kernel and user space software Background with working on embedded systems and ARM processor specific System-level debugging experience and problem-solving skills Excellent communication skills Ways to stand out from the crowd: Experience in working with the Linux and open-source software communities Understanding of the Linux power management features (scheduler, dynamic frequency scaling, runtime power management, su

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification. What we need to see: BS in Computer Science, Information Sys

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 <

Are you ready to do your life’s work at the heart of the autonomous revolution? NVIDIA’s SWQA organization is seeking a world-class Software QA Test and Tool Developer to join our Automotive Platform team, where the code you validate ensures the safety of millions on the road. In this role, you won't just be testing software; you will be architecting the security and reliability of the next generation of intelligent vehicles. We are looking for engineers who are as comfortable navigating low-level product architecture as they are deep-diving into complex product use cases with passion for quality. This is a high-impact, hands-on position focused on our industry-leading automotive products, offering a rare opportunity to influence the core of our tech stack. You will also build the tools and frameworks that define performance standards for systems running on Linux and QNX. What you’ll be doing: Design, execute, and automate comprehensive test cases and test scenarios to validate our automotive platforms using various test methodologies to identify and track actionable defects and track them to closure. Participate in deep-dive reviews of product requirements and technical designs, providing critical feedback to ensure features are built for testability and security from day one. Partner closely with project management, hardware teams, and software developers to provide rigorous technical analysis of bugs and publish data-driven statistical reports for global team members. Architect and maintain a distributed test automation framework capable of managing high-concurrency workloads across an extensive automation farm of hundreds of concurrent systems. Develop sophisticated test libraries and automation solutions to accelerate development cycles and expand automated test coverage for re

NVIDIA Networking team is looking for an outstanding candidate who thrives in a multifaceted environment, to facilitate managing SW Releases for our leading SW products by taking responsibility for cross projects activities. In addition, ensure releases are delivered on time and in high quality, coordinate between development and testing groups and between global SW groups. The role will require to gain good understanding of products’ dependencies. What you’ll be doing: Be an effective leader in crafting and driving a delivery of high quality SW in an efficient way. Collaborate with Engineering, Operations, Architecture and Marketing across the globe to coordinate the release of products and ensure release will meet the schedule and with high quality. In parallel, partner with the QA teams to ensure alignment of all tests between the development, verification and QA groups. Take full ownership of projects from kickoff to signoff. Manage multiple parallel releases with strong attention to detail, ensuring clarity, alignment, and consistent communication across teams while tracking dependencies, milestones, and deliverables. Maintain clear, up-to-date visibility of the release status, ensuring all stakeholders have an accurate understanding of progress, next steps, priorities, and risks at any given time. Support Senior Release Managers with release activities. Own and manage selected cross-products topics (e.g., customer bugs, release checklists, RCAs, Triage, define and improve processes). Conduct release meetings and communicate release status. Resolve issues when they appear and raise red flags when needed. Work with planning and tracking systems to lead the release progress, and build release indicators. What we need to see: Bachelor's or Master’s degree or equivalent experience in Computer Science or industrial Engineering with techn

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 &#43; 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 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'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 &#34;the AI computing company.&#34; We're looking to grow our company and establish teams with the most thoughtful people in the world. We are looking for an excellent Senior Engineering Manager to lead a large firmware engineering organization delivering end-to-end manageability firmware for NVIDIA's next generation Data Center Compute Systems. This role owns HGX product line and OpenBMC-based management firmware and MCU firmware components in data center platforms, including architecture, execution, quality, reliability, telemetry, and customer readiness. We are seeking an experienced senior leader with strong technical depth, broad system perspective, and a proven ability to lead large teams through complex product cycles. This role is onsite in Santa Clara, CA, USA. If you're creative and autonomous, we want to hear from you! What you'll be doing: Lead a large firmware engineering organization delivering OpenBMC based firmware and MCU firmware for next-generation Data Center Compute Systems. Own HGX platform as a lead for Firmware and System software readiness working across the organization. Define and drive the long-term firmware roadmap, balancing architectural innovation with product execution and delivery milestones. Drive architecture strategy across BMC, MCU, platform software, manageability, health management, and data center firmware interfaces. <spa

We're looking for a Principal Software Engineer to join our CSP Engagements team as the technical focal point for GPU firmware and GPU system software, working directly with engineering teams of key CSP / hyperscale customers to ensure they can reliably manage, update, and operate NVIDIA GPU firmware at fleet scale. You will drive work streams with engineering teams of key CSPs/hyperscale customers to build shared understanding of GPU firmware and system software integration, incorporate their feedback into NVIDIA's feature roadmap and delivery plan, and ensure customer-side automation and recovery procedures are ready before each firmware release. Your cross-CSP visibility enables you to identify patterns in GPU firmware operational challenges that drive systemic improvements no single customer engagement could surface alone. What you'll be doing: Drive GPU firmware & siftware work streams with CSP engineering teams — ensuring they understand GPU firmware architecture (VBIOS, InfoROM, microcontroller firmware), update sequencing, recovery procedures, and GPU power management Gather and synthesize CSP feedback on GPU firmware/software — covering manageability, observability, security requirements (e.g., multi-tenancy isolation, secure boot, attestation), and performance — and champion those priorities into NVIDIA's GPU firmware/software feature roadmap and delivery plan Drive GPU firmware update orchestration for large-scale deployments — multi-GPU update sequencing, rollback strategy, failure handling, and validation across hundreds of GPUs per rack Serve as the technical focal point between NVIDIA and CSP firmware/software engineering — ensuring GPU behaviors (error recovery flows, thermal protection, power state transitions) are well-documented and accessible for customer integration Identify cross-CSP GPU SW/FW issue patterns — common update failu

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,