Nvidia Manager Jobs

NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling. Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods. In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD wi

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 the 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 Developer Technology Engineer you will be at the forefront of innovation, working with leading industry partners and exciting OSS projects to accelerate RTX & DGX SoC performance for agentic use. This role offers an outstanding opportunity to collaborate with world-class talent and make a significant contribution to the next era of enterprise and consumer AI. What you'll be doing: Own key engagements with our fast-paced developer ecosystem partners, optimizing their applications to deliver outstanding end-to-end performance on RTX and DGX SoCs. Take ownership of performance optimization for compute-intensive CPU, AI, and 3D graphics workloads, working with domain experts to identify bottlenecks and implement effective solutions. Work across system software, GPU driver, architecture, and NVIDIA Research teams to influence next-generation, high-performance SoC platforms by bringing real-world workflows and actionable insights from partner and customer needs. Provide technical guidance and mentorship to junior engineers while contributing to an inclusive and high-performing team environment. What we need to see: BS or MS degree in Computer Science, Engineering, Mathematics or related degree (or equivalent experience) 5+ years of respective work experience as software developer Proficiency in C/C++, Python, software

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s an outstanding legacy of innovation that’s fueled by great technology—and outstanding 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. Our team is looking for Senior System Engineers specializing in self-driving vehicle technology. As a senior member you will be responsible for integrating and maintaining end-to-end software with Sensing/Perception/Localization/Planning/Control included, ensuring its stable and safe deployment in the field. What you'll be doing: Develop and maintain the application as well as vital tools for autonomous driving Diagnose and tackle real exciting problems to provide the world with the best driving experience Vertical stack performance optimization What we need to see: BS/MS or higher in computer science or a related engineering field Excellent C and C++ programming 5+ years of relevant proven experience Experienced in developing system software in user space with capability digging into kernel and even low-level hardware Good understanding of Operating Systems, threading, synchronization and parallel computing to build highly efficient applications Familiar with underlying parallel architectures, CPU/GPU/DLA/DSP Excellent analytical, communication and collaboration skills in international organization Ways to stand out from the crowd: Software development experience with CUDA Prior experience in: Autonomous vehicles, Robotics, Computer Vision and/or ML Understa

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. Join NVIDIA's GPU Performance Infrastructure team and be part of a brand-new journey in validating and shipping next-generation GPU architectures. At NVIDIA, we empower our engineers to innovate and drive powerful performance through innovative infrastructure and workflows. This role is uniquely positioned to influence the entire lifecycle of GPU performance verification, from early-stage modelling to post-silicon validation. With our bold standards and extraordinary team, you'll have the chance to define a significant impact on the future of computing! What you'll be doing: Build and develop end-to-end performance verification infrastructure. Build scalable data pipelines to surface performance metrics from simulation, emulation, and silicon environments. Coordinate with GPU architects to craft infrastructure for performance verification of upcoming architectures. Work closely with HW teams to automate and accelerate verification workflows, enabling faster GPU build iteration. Empower GPU architects by providing insights to understand current performance and model industry-leading performance for future builds. Improve the daily workflows of the wo

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! We are the Silicon Power Team within the Silicon Co-Design Group. We architect and deliver groundbreaking solutions for productizing NVIDIA's chips across consumer, professional, server, embedded, mobile, and automotive markets. Silicon characterization, correlation to arch and design expectations, product spec finalization, and productization techniques and infrastructure are our day-to-day work — always on the bleeding edge of the industry. Small decisions here have outsized impact on performance, efficiency, reliability, bring-up speed, and ultimately what the product delivers in the field. We are hiring a Senior Silicon Power Engineer to own power-feature productization on a flagship silicon program. This is not a coordination role, and it is not a compliance role — it is the seat where power features either work at scale or become the reason a program slips. The two highest-leverage problems in this seat: Close the hardest multi-functional power failures before they gate a program. Take ambiguous, cross-boundary issues across architecture, firmware, validation, and platform to root-cause closure — with productized fixes and reusable methodology the next program can inherit. Build AI-enabled characterization as a real capability, not a demo. Every bring-up generates terabytes of characterization, shmoo, and telemetry data. Deploy AI workflows for data analysis, metric extraction, trend detection, and cross-bring-up correlation — with the guardrails and validation discipline to make them trustworthy enough to gate production decisions! <

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 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 & SOC acts as the brains of computers, robots, and self-driving cars that can understand the world. We are looking for Design Validation Engineer in Taipei for board/system power qualification and function test, responsible for NVIDIA Data Center platform, Graphics board, ARM Based platform and Autonomous Driving Platform. If you're creative and autonomous, we want to hear from you! What you'll be doing: Server/Motherboard/Mobile system functionality test. Clock/Sequency/GPIO signal measurement and verification. WAT (wide area test) function test. Gaming test. High/Low speed interface SI test. Co-work with hardware design engineers on debug and FA. Co-work with mechanical/thermal engineers for cooler/heatsink design. What we need to see: Masters degree in EE, computer science, or relative majors. Proficient with Linux system and GPU setup. Capable of writing simple shell scripts and analyzing test results using commands. Familiar with PC and Datacenter system hardware assembly, MB BIOS upgrade, and network troubleshooting Proficient with a programming language (C/C&#43;&#43;, Python, Java, or Perl) Understand UEFI boot OS startup process and out-of-band (

We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform. This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations. What You Will Be Doing: Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale. Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams. Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals. Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation. Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams. Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness. Provide technical leadership and mentorship, influence engineerin

We are seeking a highly skilled and experienced Staff Network Site Reliability Engineer (SRE) to join our Enterprise Network Operations and SRE team. In this role, you will be pivotal in implementing our vision for a reliable and efficient network infrastructure. The ideal candidate is passionate about network operations and committed to enhancing the user experience. You'll have the opportunity to solve complex network challenges using hands-on debugging and by focusing on network automation, observability, documentation, and operational excellence. This is a critical position focused on ensuring user satisfaction and brilliance in network operations. What you'll be doing: Owning the operational aspect of the network infrastructure, ensuring its high availability and reliability, actively working on network incidents and service requests. Partnering with architecture and deployment teams to guarantee that new implementations are supportable and align with production standards. Advocating for and implementing automation to reduce toil and improve operational efficiency. Minimizing manual operational tasks to achieve and maintain Service Level Objectives (SLOs). Monitoring network performance, identifying areas for improvement, and collaborating with relevant teams to implement refinements. Proactively identifying and mitigating network risks to promote continuous improvement. Collaborating with domain experts across functions to resolve production issues swiftly and effectively, ensuring customer happiness. Conducting blameless postmortems and following through on Root Cause Analyses (RCAs). Discovering opportunities for operational improvements and teaming up with colleagues to devise solutions that enhance excellence and sustainability in network operations. Developing knowledge base articles for automa

We're looking for a Principal Engineer to join our CSP Engagements team as the technical focal point for end-to-end performance, working directly with engineering teams of key CSP/hyperscale customers to ensure they achieve various performance targets on NVIDIA platforms. In this role, you will augment NVIDIA's performance and benchmark teams with a dedicated CSP-facing focus. You will drive work streams with CSP engineering teams to build shared understanding of platform performance characteristics, gather and incorporate their workload-specific feedback into NVIDIA's optimization priorities, and validate that performance targets are met in customer-representative configurations. Your cross-CSP visibility enables you to identify patterns and drive systemic improvements in documentation, configuration guidance, and tooling. What you'll be doing: Drive performance characterization work streams with engineering teams of key CSP/hyperscale customers — ensuring they understand platform performance expectations, profiling methodology, and tuning options for their specific workloads Gather and synthesize CSP performance feedback — identify gaps between expected and actual throughput, and champion optimization priorities back into NVIDIA's CUDA, NCCL, driver, and firmware teams Ensure key open-source performance and stress tools (e.g., STREAM, GPU Burn, GPU BLAST) are updated and validated for the latest NVIDIA rack-scale systems, GPU architectures, and CPU platforms — so customers and internal teams have reliable baseline measurements from day one Work closely with CSPs to ensure their own performance and validation tooling reflects the latest GPU capabilities, memory hierarchy changes, and platform-specific tuning parameters Conduct cross-CSP performance comparison and pattern analysis — identify configuration, software, or workload differences that explai

We are looking for a highly motivated AI/ML Software Engineer to join the Enterprise Agentic AI Platform team within IT. You will work closely with Business Analysts, and Engineering teams to design, develop, and deploy enterprise AI solutions that improve productivity and automate business workflows across Engineering, Operations, and Manufacturing. What you'll be doing: Design, develop, and deploy Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks. Build scalable AI services and reusable components integrated with enterprise applications such as PLM, SAP, and other business systems. Collaborate with business and IT teams to translate business requirements into AI-driven solutions. Develop secure, scalable APIs and enterprise integrations to enable intelligent workflows and automation. Improve AI solution quality, performance, and reliability through prompt engineering, evaluation, and continuous optimization. Partner with cross-functional teams throughout the Software Development Lifecycle (SDLC), from solution design through deployment and production support. What we need to see: Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field. 6&#43; years of software engineering experience with strong proficiency in Python and backend application development. Hands-on experience with Generative AI, LLMs, RAG, AI agents, REST APIs, and cloud-native application development. Experience integrating enterprise applications and building scalable, production-ready software solutions. Strong analytical, problem-solving, communicatio

We are seeking software engineers to work on next-generation graphics and computing products. Our charter is to build the most stressful set of applications a GPU or high performance computing server would see in its life cycle. The best candidates will have strong C&#43;&#43; programming skills, thorough knowledge of graphics concepts and algorithms, a solid foundation of systems software with emphasis on OS fundamentals, and a deep understanding of current generation PC/hardware architecture. Excellent communication skills and a dedication to meticulous engineering practices are a requirement. As a system software engineer, you will extensively use your knowledge of operating systems, algorithms, and computer architecture to provide robust and efficient solutions to validate and test next generation processors. What you'll be doing: Working closely with architecture, hardware and driver teams through the product development lifecycle of computing and graphics processors, as well as compute products. Responsible for crafting software tools and infrastructure required for new chip development, validation, and productization. You will assess new hardware features and architect manufacturing diagnostic tests using pre-beta CUDA and OpenGL extensions. This job will require an understanding of our hardware and software architectures. What we need to see: BS or MS degree in one of the areas of Electrical Engineering, Computer Engineering, Computer Science or equivalent experience 3&#43; years experience in a related hardware/software position Strong C/C&#43;&#43; programming skills Familiarity with P

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! Every major NVIDIA silicon product family—from the chips powering AI and datacentre systems to gaming, professional, embedded, and automotive platforms—passes through our productization work on its way to production. NVIDIA’s Silicon Co-Design Productization team works from pre-silicon strategy and feature development through bring-up, characterization, correlation, and optimization. Our charter spans power & performance modelling, bring up & tuning of low-power features, power & thermal controllers , and system-level optimization that ultimately shape how NVIDIA products are configured, binned, specified, and shipped. What you'll be doing Drive silicon power productization from pre-silicon planning through bring-up and production, including test strategy, feature readiness, characterization, and optimization. Partner with architecture and design teams to identify improvements, validate features, and help translate them into production-ready solutions. Correlate measured silicon behaviour with pre-silicon expectations, investigate gaps, and drive complex issues to root cause. Build power and performance models and characterization methodologies that decide silicon binning, product specifications, productization decisions, and customer guidance. Use AI/ML and data-driven methods to analyse characterization & telemetry data, identify anomalies & trends , and accelerate issue debug across silicon, board, power delivery, firmware,

NVIDIA Networking division is a leading supplier of innovative end-to-end InfiniBand and Ethernet connectivity solutions and services for servers and storage. We offer market-leading solutions that include adapter cards, switches, cables, and software to support networking technologies. Our products optimize Data Center performance and deliver industry-leading bandwidth and scalability. In addition, we serve a wide range of sectors including high performance computing, enterprise, Data Center, cloud computing and Web 2.0. We are constantly reinventing ourselves to stay ahead of the market and bring groundbreaking products and services to the industry. Our product line is focused on delivering the most optimized Ethernet solutions for industries like Media and Entertainment as well as any other industry that can benefit from our DataStream and TCP/IP acceleration. What you will be doing: Drive multiple early-stage design concepts of Test Equipment & fixtures while working in fast-paced product development cycles. Independently lead Test Equipment & fixtures design from concept, through detailed design, and support it during Bring-up, Qualification and Mass-Production phases. Participate and lead design and design reviews of Test Equipment & fixtures by using our CMs (Contract Manufacturers) as the designers Collaborate in research of groundbreaking technologies, materials, and processes with other groups to bring in creative ideas that address evolving needs. What we need to see: B.Sc. in Mechanical Engineering or higher degree. 5&#43; years of experience in classical mechanical design of mechanisms, jigs, fixtures, products and machines development. Knowledge and experience in automation (pneumatics XYZ motion systems, etc) and in design of machining and sheet metal parts Knowledge and experience in static analysis and simulations.

NVIDIA is seeking an a PCB Library Engineer to join our PCB Design Infrastructure team. In this role, you will help develop and maintain the PCB library assets used across NVIDIA's Data Center, AI, Networking, Automotive, and Graphics products. Working alongside experienced PCB designers, library engineers, mechanical engineers, manufacturing engineers, and component engineers, you will create and validate component footprints, schematic symbols, mechanical components, panel definitions, and other critical design assets that enable successful product development. This position provides an excellent opportunity to build expertise in PCB design, manufacturing, component engineering, and design automation while supporting some of the most advanced computing platforms in the world. What you'll be doing: Develop PCB footprints, padstacks, schematic symbols, and mechanical library content using Cadence PCB design tools. Review component datasheets, package drawings, and engineering specifications to create accurate design libraries. Support library verification, release, and documentation processes. Partner with PCB design, mechanical engineering, manufacturing engineering, and operations teams to resolve library-related issues. Learn and apply industry standards, including IPC requirements, DFM, DFA, and DFT principles. Support quality initiatives to ensure library content is accurate, manufacturable, and scalable. Participate in continuous improvement and automation efforts within the library environment. Develop a strong understanding of PCB fabrication, assembly, and component technologies. What We Need to See: BS degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, Manufacturing Engineering, or a related field or equivalent experience. <p

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. Join NVIDIA's Nemotron Harness team. We are leaders in AI research, exploring machine learning, reinforcement learning, computer vision and natural language processing. As a Research Scientist, you will work on projects that seek to redefine general intelligence. This Zürich, Switzerland position offers an outstanding platform to participate in innovative research and impact the future of AI. What you will be doing: Conduct groundbreaking research to advance the science and technology of intelligent machines. Co-develop models with harnesses, increasing task horizon, improving memory and general intelligence capabilities in VLM/LLM systems. Work towards daring long-term research goals, while identifying and achieving immediate achievements. Influence the research community through high-quality publications and collaborative efforts. Open source high-quality code and ensure the reproducibility of your research. What we need to see: PhD or equivalent 6&#43; years of experience in Computer Science, relevant technical field, or similar, completed prior to joining NVIDIA. Research background in machine l