Nvidia in United States

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 NIM team and be part of an exceptionally ambitious project in Santa Clara, CA! As a Senior Software Engineer, NIM Tools, you will have the remarkable opportunity to build a groundbreaking model customization and deployment lifecycle platform from inception. This isn't just another feature team—you will be defining the structure for a new product surface accessed by ISVs and CSPs internationally. Your work will empower customers to take models from selection through fine-tuning, evaluation, deployment, and compliance flawlessly. What you'll be doing: Compose and build the fine-tuning handoff pipeline, including LoRA adapter repackaging, re-quantization, and re-validation into NIM. Develop the evaluation harness, ensuring models meet our high standards. Implement the observability and attestation layer to produce auditable compliance artifacts. Work in close partnership with ISVs and CSPs to roll out NVIDIA NIMs on a large scale. Define and improve durable platform APIs, steering clear of one-off integrations. Ensure flawless completion of projects through strict attention to detail and proven methodologies. Wha

NVIDIA is seeking a Senior Software Engineer to help us develop distributed storage services for AI/ML. In this role you will work closely with the broader NVIDIA team to design and build a reliable, scalable, and efficient storage-as-a-service tailored to AI applications that can be deployed anywhere and scale without limitations. This service supports the whole NVIDIA critical business from graphics drivers to autonomous vehicles to deep learning frameworks. To achieve this goal, we are looking for an engineer with a deep understanding of distributed systems, outstanding design skills, and a track record in building and delivering large-scale distributed services. What you will be doing: Leading the overall architecture and design of our distributed storage service optimized for AI/ML Develop and maintain distributed, robust and scalable Go programs deployed to state of the art open-source ecosystems, including Kubernetes. Develop and maintain user-space applications, containers, Go-bindings, and CLI tools. Building features for a distributed storage service to enhance availability and reliability for large-scale deployments Engaging and collaborating with NVIDIA Research, Computing, Product teams, cross-functional teams, and external customers to deliver Cloud services. Automating distributed storage service end-to-end, including deployment, management, and monitoring What we need to see: Bachelor’s of Science in Computer Science, or related field (or equivalent experience) with 8+ years of industry experience Strong background in developing distributed systems involving Golang, Kubernetes, and Cloud Service Provider integrations Strong track record of delivering distributed services in a variety of distributed computing environments Experience in i

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle. The Hypervisor and RTOS Team within NVIDIA DRIVE Software plays a critical role in NVIDIA's expansion into the world of artificial intelligence and autonomous vehicles. Our job is to facilitate the sharing and separation of system resources while achieving real-time, safety, and security requirements. We develop Hypervisor and RTOS with a strong focus on automotive quality, safety and security needed for the real-time, highly available system level components of world-class Autonomous Vehicles. We are making extensive use of formal methods to automate our workflow and increase the quality of our SW. We are hiring now for the position of Senior System Software Engineer for Hypervisor and RTOS What you’ll be doing: Design and develop new features for RTOS and hypervisor software stack. Bring up and optimize RTOS and hypervisor stacks on new NVIDIA Tegra SoCs. Develop high-integrity software using best-in-class engineering, safety, and security practices. Debug complex system-level issues across hardware, firmware, RTOS, and virtualization layers. Lead team-wide technical initiatives by building alignment, coordinating execution, and driving them to completion. What we need to see: BS, MS in CS/CE/EE or a related engineering field or equivalent experience </

NVIDIA's GeForce Now, the next-generation gaming service powered by NVIDIA GPUs in the cloud, transforms a Mac, any PC, or just a mobile device into a high-performance gaming rig. GeForce NOW automatically keeps games up-to-date, and users around the globe can instantly stream the latest games in high-definition resolution at the lowest latency for the smoothest gameplay. Just click and play! Visit us at https://www.nvidia.com/en-us/geforce-now. In addition to gaming, the state-of-the-art low-latency streaming technology has expanded to a new range of applications, including augmented and virtual reality, artificial intelligence, and robotics. We are now looking for a Senior Software Engineer – Streaming with strong C&#43;&#43; skills and a deep interest in streaming technologies to join a team of highly skilled and motivated software engineers who help build the next generation of applications with media and data streaming capabilities. Now, are you passionate about driving this technology to its edge? Do you understand various streaming protocols? Can you solve complicated problems and propose innovative solutions? Then, we are keen to hear from you. What you’ll be doing: Design, develop, optimize, and debug C&#43;&#43; software for ultra low-latency streaming systems. Build and improve media streaming pipelines using technologies such as WebRTC, GStreamer, RTP/RTCP, and related protocols. Analyze CPU, memory, networking, media pipeline, and scheduling behavior across real-world workloads. Work across Windows, Linux, QNX, applications frameworks, and embedded platforms. Define and implement KPIs for networking quality, streaming quality, and user experience. Integrate streaming softwa

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-X Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions in AI for Chip Design and AI for Predictions in various use cases in manufacturing testing 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 on innovating in the DFT Power, Thermal & Voltage Noise Methodology areas. This will include working on groundbreaking low power & thermal solutions for our manufacturing tests to be enabled at conditions that push the boundaries for our datacenter GPUs. You will work with multi-functional teams including Product Development & Power Architecture, implementing brand-new methodologies on hard-to-solve problems for improving our outgoing quality of chips. You will work on post-silicon data analysis for power to architect the next-gen solutions. In addition, you will help develop and deploy DFT methodologies for our next generation products using Applied ML & 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 equ

At NVIDIA, we are at the forefront of technological innovation, pushing the boundaries of AI and accelerated computing. Our team in Santa Clara, CA is looking for a Senior Software Engineer in Test to join us in this exciting journey. This is a ground breaking opportunity to work with powerful technology, collaborate with a world-class team, and make a significant impact in the industry. If you are passionate about AI and quality assurance, and thrive in a dynamic environment, this role is perfect for you! What you'll be doing: Accomplishing test cases to validate NVIDIA enterprise offerings, such as NIM, NeMo, and BioNeMo. Crafting, implementing, and maintaining automated test cases and supporting automation infrastructure. Collaborating with development teams to triage issues, perform root cause analysis, verify fixes, define additional tests, and improve test plans. Investigating and bringing to bear AI capabilities to accelerate the Quality Assurance (QA) process. What we need to see: MS or PhD degree in computer science or relevant field, or equivalent experience. At least 5&#43; years of professional experience in software testing. Proficiency in oral and written English. Comfort working with Linux OS. Strong skills in shell and Python programming. Strong knowledge of QA principles and background in software testing. Experience using AI development tools for crafting test plans, developing test cases, and automating test cases. Excellent problem-solving abilities. Strong interpersonal skills, quick learning ability, proactive approach, innovation, and dedication. Self-motivation and a passion for learning new hardcore technology. Knowledge in LLM and AI models is a plus. <

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&#43;, MSEE with 3&#43;, 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&#43; years of respective work experience as software developer Proficiency in C/C&#43;&#43;, Python, software

NVIDIA builds the silicon behind AI, accelerated computing, and graphics. Every watt of performance and every degree of thermal headroom traces back to decisions made in power, performance, and thermal architecture. We are the Silicon Co-Design Group (SCG). We identify, own, and drive system-level co-design ideas. We start with initial concepts and advance to product differentiation across NVIDIA's roadmap. We are hiring a Principal System Power Management and Performance Architect who operates at the ambiguous boundary where workload behavior, silicon capabilities, firmware policies, and platform constraints collide, and who turns that ambiguity into architecture that survives across multiple silicon generations. SCG scope spans architecture, design, software, operations, platforms, and productization. This role shapes system, platform, and data center features and behavior, and partners with teams across NVIDIA. What You'll Be Doing: The work here is rarely well-defined when it arrives. You will be given problems that appear to be performance gaps or power anomalies and encouraged to build a framework for solving them, not just tackle a single instance. Define the multi-generation roadmap for system-level power and performance features, grounded in prototyping, use-case analysis, and cost/benefit trade-offs across segments. You will decide what problems are worth solving and why. Own the architecture and integration strategy for HSIO power management, DVFS, P-states, and low-power features. Your decisions improve product performance, power, and reliability across product lines — not just the current program. Lead system-level boot and IST architecture defining how power and clock domains initialize, sequence, and recover across complex multi-IP systems where the interaction space is large and the failure modes matter. Drive power management strategy at data

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

We're looking for a Principal Software Engineer to join our CSP Engagements team as the technical focal point for rack-scale system SW/FW, working with CSP engineering teams to ensure they can deploy, monitor, and operate these systems reliably at fleet scale. In this role, you will collaborate with NVIDIA's cross-functional rack-scale system SW/FW engineering teams with dedicated CSP-facing technical leadership. Your focus is on the system-level software that manages, monitors, and recovers the rack as a whole — fabric management, GPU/NVSwitch error handling and recovery, health telemetry APIs, firmware update orchestration, and SW-driven serviceability. You will drive work streams with CSP engineering teams to build shared understanding of the architecture, incorporate their operational feedback, and ensure integration readiness. What you'll be doing: Drive rack-scale SW/FW architecture alignment across CSP engagements — including fabric management software, link health monitoring, GPU/NVSwitch error handling, SW/FW serviceability features (e.g., hot-plug support, component isolation, firmware-driven recovery), and multi-component firmware orchestration Drive technical work streams with CSP engineering teams on rack-scale system software — ensuring they deeply understand fabric management, NVSwitch behavior, error handling and recovery policies, health telemetry APIs, and SW/FW-controlled recovery operation Capture and synthesize CSP engineering feedback on rack-scale system software — health monitoring APIs, SW-driven serviceability workflows, firmware update orchestration, and error recovery behavior — champion that feedback into NVIDIA's architecture decisions Collaborate with multi-functional teams to ensure customer operational requirements are reflected in system software and firmware development Identify cross-CSP patterns in rack-scale SW/FW iss

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

NVIDIA is seeking a Senior Technical Program Manager to join the CSP Engagements team, focused on deep technical engagement with hyperscale cloud service providers for NVIDIA’s next‑generation datacenter systems such as Vera Rubin NVL72. This role is intended for experienced systems and embedded software leaders—including software engineering managers, technical leads, or senior architects—who have led datacenter server and platform software programs and can operate as a trusted technical partner to hyperscale CSP engineering teams. As a member of the CSP Engagements team, you will act as the primary technical engagement leader between NVIDIA’s system software organizations and CSP platform, system software, and AI teams, ensuring alignment, readiness, and successful large‑scale deployment of NVIDIA‑based datacenter solutions. What you will be doing: Lead deep technical engagements with hyperscale CSPs as the primary NVIDIA point of contact for system software, firmware, and platform readiness for NVIDIA datacenter products. Partner directly with CSP system software, firmware, and infrastructure engineering leaders to align on software architecture, bring‑up plans, deployment readiness, and production requirements for NVIDIA‑based server and rack‑scale platforms. Represent CSP technical priorities internally, advocating for customer requirements and tradeoffs across NVIDIA’s system software, firmware, hardware, silicon, and product teams are aligned to customer needs, timelines, and constraints. Own the end‑to‑end CSP engagement lifecycle, from early technical alignment and pre‑production readiness through large‑scale deployment, escalation management, and sustained production support. Drive bi‑directional technical communication: translating CSP system‑level requirements into actionable focus areas for NVIDIA engineering teams, while clearly communicating N

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 transformed computer graphics, PC gaming, and accelerated computing for more than 25 years through exceptional technology and the people who build it. In semiconductor manufacturing, our role is to enable the ecosystem, not compete within it. We partner with fabs, equipment manufacturers, and software providers to make inspection, metrology, and manufacturing intelligence dramatically faster on the NVIDIA platform. Our team builds the software that makes this possible: models, adaptation and evaluation workflows, and deployable inference capabilities that partners integrate into their own tools. We work in environments where labeled data is limited and proprietary, distributions shift across tools and fabs, production budgets are tight, and software must operate inside air-gapped facilities. We’re seeking a Principal Systems Software Engineer for Semiconductor Inspection in Santa Clara. This is a hands-on architect role: you will define the approach, build it, evaluate it, and demonstrate the results. You will work across computer vision, time-series modeling, multimodal AI, anomaly detection, model adaptation, evaluation, and production inference. Success means technology that a fab or equipment vendor can integrate, operate, and trust—not only a successful internal demonstration. What you’ll be doing: Define and prototype AI system architectures spanning optical and e-beam inspection, wafer and mask inspection, metrology, defect review, equipment signals, and process data. Advance world foundation model capabilities for semiconductor manufacturing, including vision, time-series and multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding. Develop workflows for defect detection, classification, localization, segmentation, nuisance filtering, ADC, AD