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Senior Performance Compiler Engineer - Triton
NVIDIA's invention of the GPU 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're looking for a Senior Performance Compiler Engineer to join our team and work on the open-source Triton compiler project. This opportunity involves working with new technologies and using compilers to improve AI performance on NVIDIA GPUs. Your work will enable breakthroughs in large language models, agents, and other high-impact AI applications, accelerating both training and inference. You will be immersed in a diverse, supportive environment where everyone is inspired to do their best work, pushing the limits of what's possible. What you’ll be doing: - Investigating the latest and future NVIDIA GPU hardware architecture and programming models. - Working on the frontier of AI by understanding advanced algorithms (like attention sinks and MoEs) and numerics (like block-scaled floating point) to identify new opportunities for optimization. - Designing and implementing compiler technology using MLIR to optimize high-level kernel descriptions (written in Triton's Python DSL), with a focus on generating efficient, low-level GPU code. When vital, you'll also be able to use inline PTX to hand-tune critical code paths and extract peak performance from the hardware. - Engaging in a dynamic, iterative process of optimization—sometimes starting with the kernel, sometimes with the compiler—to find the most efficient path to peak performance. - Collaborating with teams across NVIDIA, including hardware architects and the CUDA compiler team, to influence future products and ensure we are always operating at maximum efficiency. What we need to see: - Bachelor, Masters or Ph.D. degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or a related field. - 8+ years of relevant industry experience in software development. - Demonstrated strong C++ programming and software design skills, with an emphasis on performance analysis and debugging. - Experienced in parallel programming, including CUDA/OpenCL GPU programming or other parallel models such as OpenMP. - Solid understanding of computer architecture and hands-on experience with assembly-level programming. Ways to stand out from the crowd: - Experience in tuning BLAS or deep learning library kernels. - Background in numerics and linear algebra. - Experience with machine learning compilers like TVM or MLIR. - Contributions to open-source projects, especially in the AI/ML or compiler space. - Familiarity with the latest research in AI algorithms and numerics as well as a strong track record of contributions to open-source projects, particularly in the AI/ML, compiler, or high-performance computing domains. With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Manager, AI Networking Performance Research and An...
NVIDIA is seeking a highly skilled and versatile Performance Research and Analysis Manager to join our Performance Group. This role will drive end-to-end performance strategy and execution for next-generation NVIDIA NIC, Switch, and Networking technologies, spanning the full lifecycle from pre-silicon performance modelling (simulation and emulation) through bring-up, validation, and GA readiness. The ideal candidate will lead cross-functional performance efforts across multiple teams to evaluate and optimize low-level networking and offload capabilities, including Storage acceleration, Security protocols, NIC pipeline and steering mechanisms, Switch performance, and E2E AI Networking cluster level performance for AI WLs, distributed training, and Inference jobs. In addition, this role will play a key leadership position in building scalable telemetry frameworks, performance dashboards, and job-level monitoring solutions to enable continuous performance tracking and root cause analysis across NVIDIA supercomputing environments. The position also includes deep ownership of competitive benchmarking and performance analysis. You will work closely with a wide range of NVIDIA hardware and software platforms, including HCAs, DPUs, switches, CPUs, GPUs, and full system architectures, across multiple networking stacks and performance-critical software layers. What you'll be doing: - Lead performance research and evaluation of advanced networking technologies supporting AI workloads, including LLM training and inference at supercomputing scale. - Define end-to-end performance test plans and methodology for next-generation Networking HW and networking technologies, including performance expectations and target KPIs. - Drive benchmarking, profiling, reporting, and deep performance characterization of networking workloads and offload features. - Collaborate closely with simulation, architecture, chip-design, firmware, and software teams to assess performance tradeoffs and identify bottlenecks. - Perform deep root cause analysis (RCA) for performance gaps and stability issues, and drive cross-team mitigation plans. - Develop and enhance performance analysis tools, automation frameworks, and scalable methodologies for cluster-level performance evaluation. - Own performance observability efforts, including telemetry pipelines, dashboards, and job-level performance analytics. What we need to see: - B.Sc in Computer Science or Software Engineering - 5+ years of experience with high-performance Networking technologies (RDMA, Storage, Security, OVS, MPI) - 3+ years as an engineering team manager - Demonstrated Performance Analysis skills and methodologies. - Experience with Cluster level performance, Telemetry, NIC, DPUs, Switches, and GPUs. - Fast and self-learning capabilities with strong analytical and problem solving skills - Programming Languages: Python, Bash and C/C++ languages - Experience with Linux OS distros - Team player and a leader with good communication and interpersonal skills Ways to stand out from the crowd: - Deep system-level architecture knowledge (Intel / AMD / ARM CPUs, NVIDIA GPUs, HCA/DPU architecture, memory subsystems, PCIe, storage, NVLink). - Strong expertise in RDMA networking performance and AI communication stacks (e.g., NCCL). - Proven experience analysing AI workload communication patterns and benchmarking distributed LLM training workloads at scale. - Experience designing telemetry frameworks, monitoring pipelines, and performance dashboards for large clusters. - Familiarity with modern AI tooling including performance-driven agents, automation pipelines, and RAG-based applications. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. LI-Hybrid
Senior Solutions Architect, Generative AI
NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Computing and Deep Learning (DL) software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement? You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts focused on Generative AI and Large Language Models (LLMs). You will also collaborate with a diverse set of internal teams on performance analysis and modeling of inference software. You should be comfortable working in a dynamic environment, and have experience with Generative AI, LLMs, and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA! What You Will Be Doing: - Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions - Dynamically engaging with developers, scientific researchers, data scientists, which will give you experience across a range of technical areas - Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform - Working closely with customers to help them adopt and build solutions using NVIDIA technology - Analyze performance and power efficiency of deep learning inference workloads - Some travel to conferences and customers may be required What We Need To See: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow - Strong fundamentals in programming, optimizations and software design, especially in Python - Strong problem-solving and debugging skills - Excellent knowledge of theory and practice of Large Language Models and Deep Learning inference - Excellent presentation, communication and collaboration skills - Desire to be involved in multiple diverse and creative projects Ways To Stand Out From The Crowd: - Experience with NVIDIA GPUs and software libraries, such as NVIDIA NeMo Framework , NVIDIA Triton Inference Server , TensorRT , TensorRT-LLM - Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design - Familiarity with parallel programming and distributed computing platforms - Prior experience with DL training at scale, deploying or optimizing DL inference in production Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Power Architect - New College Grad 2026
Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! What you'll be doing: - You will be working on architecting GPU power features and system level power management solutions for NVIDIA products. - Collaborate closely with other Architects, Software Engineers, ASIC Design Engineers, and Product teams to study, devise and implement the power management strategy for NVIDIA's GPU roadmap. - Research and develop solutions to address complex energy efficiency problems for various GPU use-cases such as: Deep Learning training, ADAS, Gaming, Video Playback, and Idle. - Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs and platforms. What we need to see: - Pursuing or recently completed a MS or PhD in Electrical or Computer Engineering (or equivalent experience) - Knowledge of performance simulators/monitors and Low Power architectures/techniques a plus. - Working knowledge of Python, and frameworks/packages like: TensorFlow, Pandas, NumPy, PyTorch a plus. - Exposure to tools/flows such as Design Compiler, PTPX, and Power Artist etc a huge plus. - Experience with lab setup and measurement using equipment such as scope/DAQ is helpful. Ways to stand out from the crowd: - A master’s degree/internship with a focus/projects in Low Power Architecture, power modeling, and deep learning is a plus! 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. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Engineer - AI Agents and Systems
Artificial intelligence is moving from passive assistance to autonomous, always-on agentic workflows. Our mission is to make this transition flawless, high-performing, and secure for millions of users worldwide. We are looking for a Senior Engineer to serve as a key technical leader in deploying advanced AI agent frameworks and local runtimes to Windows and NVIDIA GeForce RTX GPUs. You will lead the development to ensure open-source AI agents (like Nemoclaw and OpenClaw) run locally, safely, and efficiently on consumer PCs. By combining powerful local inference (Nemotron models) with robust privacy routers and sandboxed execution, you will help create the foundation of the desktop AI operating system. What You Will Be Doing: - Act as the lead engineer for developing the agent frameworks natively on Windows environments. You will shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops. - Lead the engineering efforts to optimize the agent runtimes for Windows. You will ensure that autonomous agents operate within thorough, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress). - Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community. Ensure our consumer hardware provides an excellent ecosystem for autonomous agents. - Foster a collaborative engineering culture by mentoring other engineers, establishing best practices for AI agent deployment, and writing reliable, production-ready code. What We Need to See: - 10+ years of relevant professional software engineering experience, with at least 3+ years in Staff, or Lead Architect role. - BS, MS, or PhD in Computer Science, Computer Engineering, or a related technical field (or equivalent experience). - Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture. - Proven understanding of LLM inference pipelines (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware. - Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools. - Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic). - Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most talented people on the planet working for us. As part of our team, you will have the opportunity to influence the future with your vision and expertise. Are you creative? Are you driven not just by data or the need to know why, but yearn to ask, 'why not'? We want to hear from you. With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Developer Relations Manager, Physical AI Me...
Are you a visionary at the intersection of AI innovation and executive influence? Do you thrive on shaping the future of visual understanding and AI-driven operational intelligence? If you’re a bold, strategic problem solver with deep technical expertise in modern computer vision, foundation models, and AI agents — this is your opportunity to lead from the front and help redefine what’s possible in the world of Physical AI. As a Senior Developer Relations Manager for NVIDIA Metropolis, you’ll be a key force driving the adoption of next-generation AI technologies that transform how cities, industries, and infrastructure think, see, and act. You’ll engage with innovative ISVs, global enterprise leaders, and ecosystem partners to unlock the full potential of visual understanding and automation. This is your chance to be a trailblazer in an era where perception meets reasoning, helping to accelerate the evolution from traditional AI pipelines to multimodal Vision-Language Models (VLMs) and intelligent agents capable of real-world decision making. What You’ll Be Doing - Identify, build, and guide strategic relationships across the AI ecosystem, from startups to enterprise CEOs, driving real-world adoption of NVIDIA’s advanced Vision AI and VLM capabilities - Engage developers and partners working on video analytics, perception, and AI agent use cases to bring breakthrough use cases to life - Provide hands-on technical leadership, augmenting CNN-based models with Vision Language Model (VLM) architectures into applications for video understanding, safety, operational intelligence, etc. - Partner closely with NVIDIA’s engineering, product, and marketing teams to guide developers and accelerate innovation within intelligent environments - Lead thought leadership discussions and get-to-market strategies to expand NVIDIA’s footprint in next-generation visual computing and AI ecosystems What We Need To See - Deep technical expertise in AI and computer vision, including hands-on experience with CNN architectures, Vision-Language Models (VLMs), and AI agent systems - Proven track record working directly with executive collaborators (C-suite, CTOs, founders) to shape technical strategy and drive measurable business outcomes - Strong background in AI for video understanding, public safety, ITS, industrial operational intelligence, safety compliance, or related domains - 8+ years of experience in technical roles that bridge innovation, strategy, and relationship management - Bachelor’s degree or equivalent experience in Computer Science, Engineering, or related field (Master’s or Ph.D. highly preferred) - Exceptional communication, executive presence, and ability to navigate complex technical and business dynamics Ways To Stand Out From The Crowd - Experience building and deploying AI solutions for physical environments — robotics, manufacturing, intelligent spaces - Familiarity with NVIDIA platforms such as Metropolis, DeepStream, CUDA-X, Omniverse - Proven success in empowering developer ecosystems and accelerating partner adoption in emerging AI fields
Senior HPC Performance Engineer
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. Come work for the team that brought to you NCCL, NVSHMEM & GPUDirect. Our GPU communication libraries are crucial for scaling Deep Learning and HPC applications! 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 - Collaborate with a very dynamic team across multiple time zones What we need to see: - M.S. (or equivalent experience) or PHD in Computer Science, or related field with relevant performance engineering and HPC experience - 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM) - Experience conducting performance benchmarking and triage on large scale HPC clusters - Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) - Implement micro-benchmarks in C/C++, read and modify the code base when required - Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python - Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker) - Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones Ways to stand out from the crowd: - Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control - Experience debugging network issues in large scale deployments - Familiarity with CUDA programming and/or GPUs - Experience with Deep Learning Frameworks such PyTorch, TensorFlow NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 221,250 PLN - 383,500 PLN for Level 3, and 292,500 PLN - 507,000 PLN for Level 4.
Senior Automotive Software Program Manager
Step into the future with NVIDIA, a global leader in AI computing, data science, and graphics, driving innovation in Artificial Intelligence, Deep Learning, and Autonomous Vehicles. Our team of visionaries is reshaping industries worldwide with cutting-edge technologies. Join us on an exhilarating journey as a Senior Software Program Manager to join our collaborative and fast-paced customer interfacing automotive software organization. In this role, you will be supporting our Korea n partners closely to integrate, adapt and test our NVIDIA DRIVE Software solutions, including DRIVE OS, NDAS and Alpamayo. NVIDIA is synonymous with innovation, boasting trailblazers who are shaping the world with their forward-thinking approaches. This is your chance to be part of a vibrant community that's redefining the technological landscape. Ready to shape the future of automotive technology with NVIDIA? Apply now to be part of a team that's revolutionizing the industry and driving innovation to new heights. Your potential awaits! What you’ll be doing: - Lead the lifecycle of NVIDIA’s DRIVE programs with our Korea n automotive partners. Align on timelines and contents for SW deliveries incl. those of NVIDIA’s DRIVE OS, NDAS and Alpamayo software stacks. - Coordinate with cross functional teams in South Korea , India, China, and the U.S. to resolve program issues and drive product launches. - Act as the first point of contact and first level of escalation for our automotive partners and internal senior leadership, providing updates and bringing management focus on important issues. - Align on program vehicle and system level requirements, coordinate the review, exchange, and negotiation of them. Work closely with internal software groups to understand the design and implementation - Track and prioritize know issues and bugs, allocate fixes to upcoming SW releases, track verification, and root cause analysis. What we need to see: - General knowledge about Artificial Intelligence, LLMs, Transformers, CPU/GPU architectures, etc. - General knowledge of program management concepts (task planning, agile methodologies, risk management, etc.) - Degree from a leading university or equivalent experience in an engineering or computer science related field (BS; MS or PhD). - 6+ years of work experience in automotive software development. Preferably on ADAS and AV. - Understanding of autonomous vehicle systems, sensor technologies, vehicle bus communication standards, SoCs and embedded software principles. - General knowledge of C/C++/Python, QNX and/or Linux OS. - Understanding of build pipelines, repositories, CI/CD, containerization, etc. - Proven experience of having led complex automotive programs to series production. - Excellent communication and organization skills, good time management, and task prioritization . - Willingness to regularly attend customer meetings at NVIDIA's partners’ sites. Ways to stand out from the crowd: - Experience with Automotive SPICE, ISO26262, 21448 standards. - Hands on experience developing complex embedded C++ based systems. - Fluency in Korea n - A wide existing network of contacts in the local automotive ADAS and AV industry 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. If you're creative, hardworking and proactive, we want to hear from you! 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.
Senior Signal and Power Integrity Engineer - Hardw...
We are now looking for a Senior Signal & Power Integrity Engineer! 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 tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Work on crafting creative Signal Integrity solutions to complex system design problems - System-level signal integrity simulations of high-speed NVlinks 200Gbs+, USB-4, PCIe5, GDDR6, LP5X - Modeling of vias, connectors, sockets and various system components in 3D EM tools. - Design and optimize Power Delivery Network (PDN) across packages and PCBs. - Constant improvements of SI/PI models through lab measurements - Simulation automation, data gathering, analysis and visualization using JMP, MATLAB or similar tools. - Opportunity to work in dynamic cross-functional role to optimize package, PCB, ASIC, mixed signal circuit What we need to see: - BS/MS-Electrical Engineering or equivalent experience. - 3+ years of industry experience. - SI/PI work on one or more signaling standards like PCI express, USB, SATA, HDMI, HBM, DDR5, GDDR6, LPDDR5X - Hands on use of 3-D modeling tools like ANSYS HFSS/Q3D and 2.5-D with ANSYS SIWAVE or similar. - Experience with PDN evaluation using layout extraction tools for packages and PCBs and spice-based time domain simulations. - Background with a system level timing or loss budget including silicon, package and board impairments. - Familiarity with use of VNA, TDR, DSO, ParBERT and use of applications like JMP, Matlab will be a plus Ways to stand out from the crowd: - Expertise in one or more of the high speed interface SI/PI design on any industry standard system platforms. - Experience with lab measurements, debugging, SI lab correlation using oscilloscope/ spectrum analyzer/ VNA. - Knowledge of circuit design, board/pkg component design, link architecture, timing budget methodologies LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Signal and Power Integrity Engineer - New College...
We are now looking for a Senior Signal & Power Integrity Engineer! 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 tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Work on crafting creative Signal and Power Integrity solutions to complex system design problems. - System-level power integrity simulations of high-performance AI systems, graphic cards, and Tegra systems. - Work closely with VLSI power teams and package/board design teams to design, optimize, and model power delivery networks (PDN) including dies, packages, boards, and voltage regulators. - Package and board PDN guidelines creation, review, and post layout PI extractions. - Opportunity to work in a dynamic cross-functional role to optimize package, PCB, ASIC, mixed signal circuit. What we need to see: - Pursuing MS/PhD in Electrical Engineering or equivalent experience. - Strong technical background in applied electromagnetics, transmission line theory, and signal processing is highly valued. - Experience in power integrity for core power or I/O power. - Strong understanding of how die/package/board decoupling impacts power supply noise across different frequency ranges. - Knowledge of on-die current di/dt control techniques such as dynamic clocking and throttling. - Familiarity with the SIMPLIS tool for regulator modeling; experience in modeling the behavior of on-die di/dt control techniques is highly preferred. - Hands-on experience with PowerSI, 3D modeling tools such as ANSYS HFSS/Q3D, 2.5D tools such as ANSYS SIwave (or similar), and 2D tools such as Ansys 2D Ways to stand out from the crowd: - Good understanding of how regulators work and expertise in regulator modeling. - Knowledge of package/board/decoupling capacitor technology & design. - Scripting for analysis automation 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. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Server RAS Engineer
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 “the AI computing company.” We are looking to grow our company and establish teams with the most thoughtful people in the world. NVIDIA DGX, HGX, and MGX systems deliver the world's leading solutions for enterprise AI infrastructure at scale. We are seeking a dedicated and experienced RAS (Reliability, Availability, and Serviceability). Senior Engineer. You will be responsible for improving the reliability of NVIDIA GPU and Grace systems by designing, architecting, and implementing robust RAS features. You will collaborate with multi-functional teams, including hardware engineers, system architects, and software developers, to compose architecture that meets strict reliability standards and provides outstanding customer experiences. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement. What you will be doing: - Design, architect, and deliver server-level RAS for NVIDIA’s data center products. - Define RAS requirements that ensure compliance with industry standards and customer expectations for scale-out environments. - Develop fault detection, isolation, and recovery mechanisms to ensure system resilience and minimize downtime. - Evaluate and select appropriate technologies and components to optimize reliability, availability, and serviceability, considering factors such as mean time between failures (MTBF), mean time to repair (MTTR), and total cost of ownership (TCO). - Collaborate with customers, vendors and suppliers to assess and integrate their RAS-related solutions into the overall system architecture. - Conduct system and cluster level simulations, analysis, and testing to validate and verify the effectiveness of the RAS architecture and its components. - Stay up to date with the latest advancements in RAS techniques, fault tolerance mechanisms, and industry trends to guide future system designs. - Work with NVIDIA partners on RAS related architecture and discussions to improve their use of NVIDIA products. - Work on all phases of product development, from product definition, architecture, and design, through implementation, debugging, testing and early customer support. What we need to see: - BS, MS, or PhD or equivalent experience in EE/CS or related field of education with demonstrated experience of 10+ years - Strong python programming in Linux operating environment, strong understanding of Linux kernel internals, strong code review skills. - Extensive knowledge in system-level architecture invention, reliability engineering, and fault tolerance mechanisms, optimizing RAS architectures for complex computing systems, data centers, or critical applications. - Proficient in scale-out architectures, hands on experience are a plus. - Proficiency in system-level simulation tools and methodologies (e.g., fault injection, reliability block diagrams, failure rate analysis). - Excellent problem-solving skills, attention to detail, and the ability to analyze complex system-level issues. - Possess excellent written and oral communication skills, excellent work ethics, a deep sense of collaboration, love to produce quality work and commitment to finishing your tasks every single day. - You are a self-starter who loves to find creative solutions to complicated problems. Ways to stand out from the crowd: - Consistent track record of doing RAS at platform level - Familiar with In-depth understanding of the interaction of machine check architecture and error flows with system firmware/software. - Hands on with x86 or ARM system architecture. 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 on the planet working for us. If you are creative and autonomous, we want to hear from you!
Senior Software Engineer, AI Resiliency
We are now looking for a Senior Software Engineer for AI Resiliency! At NVIDIA, we are pushing the boundaries of what’s possible in AI. We are currently seeking a Senior Software Engineer to lead the development of AI software resiliency for the most powerful AI supercomputers in the world. As a member of our AI Software Resiliency team, you will play a pivotal role in defining and implementing critical resiliency features for AI supercomputers at a scale of 100,000+ GPUs. Your expertise will be crucial in driving down cluster downtime towards zero, ensuring that our AI systems remain robust and reliable at all times. What You’ll Be Doing: - Develop AI Software Resiliency Features: Implement and optimize software features that improve AI system reliability at a massive scale, such as fast checkpoint-recovery, error detection, error isolation, and straggler/hang detection. - Hands-On Coding & Optimization: Contribute to large-scale distributed systems with high-quality, production-level C++ and Python code. Enhance performance for AI workloads running on thousands of GPUs. - Fault Tolerance & Debugging: Work on AI system error handling, implementing techniques to detect silent data corruption (SDC) and other failure scenarios. Assist in developing monitoring tools for proactive failure mitigation. - Collaborate Across Teams: Work closely with senior engineers, AI researchers, and hardware/software teams to integrate resiliency features into AI frameworks like PyTorch and JAX/XLA. - Testing & Automation: Develop and implement tests to ensure robustness, scalability, and efficiency of resiliency mechanisms. Contribute to CI/CD pipelines to automate validation of AI workloads. - Support Production Deployments: Assist in debugging and performance tuning large-scale AI workloads in cloud and HPC environments, ensuring seamless operation of AI training and inference workloads. What We Need to See: - You've achieved a Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience. - Proficiency in C++ and Python , with experience in writing efficient, high-performance code. - 6+ years of relevant experience - Strong understanding of distributed systems concepts , parallel programming, and fault tolerance in large-scale computing environments. - Familiarity with AI frameworks such as PyTorch, JAX/XLA, TensorFlow, or similar. - Experience with debugging and profiling tools (e.g., gdb, perf, valgrind, NVIDIA Nsight). - Excellent problem-solving skills and ability to work in a fast-paced, highly collaborative environment. Ways to Stand Out From the Crowd: - Hands-on experience in training models or working with model training teams . - Hands-on experience with CUDA, NCCL, or MPI for GPU-accelerated computing, especially at extreme-scale . - Knowledge of checkpointing strategies, error mitigation, or fault-tolerant computing in AI training. - Experience working with large-scale AI clusters, HPC environments, or cloud-based AI workloads . - Strong systems programming skills and experience with low-level performance tuning. As part of the AI Resiliency team at NVIDIA, you’ll work alongside world-class engineers solving some of the hardest challenges in AI infrastructure. You’ll have the opportunity to contribute directly to making AI training and inference more reliable, scalable, and efficient. If you're passionate about AI, distributed systems, and high-performance computing, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Physical Design Engineer
We are now looking for a motivated Physical Design Engineer to join our dynamic and growing team. If you want to challenge yourself and be a part of something great, join us today! 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 which are hard to tackle, that only we can pursue, and that matter to the world. This is our life's work, to amplify human inventiveness and intelligence. What you'll be doing: - Drive physical design and timing from netlist to gds. - Partner with mixed signal teams to integrate Analog IO’s and macros. - Work on multi-mode and multi-corner timing closure, RC extraction, Cross talk, IR drop and EM analysis. - Work with the Front-end teams to create and update timing constraints. - Perform Physical verification DRC, ERC, LVS, Antenna checks and other checks. - Debugging timing violations and implementing functional, Timing ECO’s and perform formal verification. What we need to see: - BS (or equivalent experience) in Electrical or Computer Engineering with 5+ years' experience or MS (or equivalent experience) with 2+ years' experience in physical design. - Experienced in Synopsys or Cadence place and route, physical design and timing tools. - Ability to form methodologies and automate flows. - Scan insertion and DFT knowledge is a plus Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Machine Learning Applications and Compiler...
NVIDIA is seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms. This is your chance to be part of something outstandingly innovative! What you’ll be doing: - Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization. - Define and implement mappings of large-scale inference workloads onto NVIDIA’s systems. - Extend and integrate with NVIDIA’s SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms. - Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware. - Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points. - Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors. - Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues. What we need to see: - MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 6 years of relevant experience. - Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency. - Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation. - Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations. - Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX. - Solid understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors. - Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements. - Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams. - Ideal candidates will have direct experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads. Ways to stand out from the crowd: - Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale. - Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability. - Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar. - Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments. LI-Hybrid
Senior Circuit Methodology Engineer
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're looking to grow our company and build our teams with the smartest people in the world. Join us at the forefront of technological advancement. We are looking for a Senior Circuit Methodology Engineer that will work closely with Nvidia's circuit design engineering team in the area of infrastructure support as it pertains to circuit design and methodology. The engineer will own and evolve the compute and GPU infrastructure in coordination with our Farm, IT, CAD, and GPU infrastructure teams. The stability and management of these resources underpins our mixed‑signal design and verification flows. This position carries a critical responsibility across the whole circuit design department and impacts the whole company’s farm infrastructure! What you'll be doing: - We need someone who will design, develop, and maintain circuit design and verification flows that run on large‑scale compute and GPU farms located across geographies through various job schedulers. These responsibilities will include: - Proactively monitor farm health and job behavior, identify bottlenecks, and implement solutions to improve throughput, utilization, and turnaround time. - Bring up and release new compute and GPU infrastructure to be used by the team. - Evaluate and qualify new compute and GPU resources, schedulers, and related EDA infrastructure components. - Build automation and tooling to streamline flow setup, job submission, resource allocation, logging, and reporting. - Track important measurements (utilization, queue times, failure rates) and lead ongoing improvement projects for farm efficiency and cost effectiveness. - You would also be required to provide user support, which may include: debug flow, infrastructure, and job‑scheduling issues; root‑cause failures; and implement permanent fixes rather than one‑off workarounds. - Additionally, you will be asked to develop and maintain documentation, training materials, and best‑practice guidelines for users of the circuit design compute and GPU environment. We also want to proactively include information into our in-house Ais in order to provide first pass user assistance. What we need to see: - BSEE, BSCE or equivalent experience. - Mid-level of programming skill is a must (primarily Python and Perl). - 8 plus years of working experience related to circuit design methodology using Cadence/Synopsys based system (Virtuoso/Custom Compiler, respectively). Previous design experience is a huge plus. - Experience with job schedulers / compute farms, primarily LSF and Slurm. - Proven ability to debug complex multi-layer issues spanning flows, scripts, tools, and infrastructure. - Strong communication skills and ability to partner with diverse engineering teams. - Exposure to circuit design workloads will be beneficial. NVIDIA is renowned as the leader in AI computing and one of the world’s most innovative and desirable employers. MSDV team consists of individuals who demonstrate outstanding creativity and critical thinking skills, driving innovation forward. If you're passionate, creative, and eager to work on the cutting edge of technology, this is the perfect team for you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Signal and Power Integrity Engineer
We are now looking for Signal & Power Integrity Engineer. 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 tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Drive board/system level signal and power integrity requirements - Lead board/system SI/PI design activities, including PCB stackup/material selection, design guide implementation, layout review, and post-layout analysis - Work closely with Architecture, ASIC, Mixed Signal, Package, and PCB Design teams to design and ensure system SI/PI performance meets expectation before Gerber out, also work closely with Design Validation teams to support SI/PI failure analysis - Develop novel algorithms & new methodologies to improve SI/PI modeling efforts - Work with Application Engineering teams to support customers w/ SI/PI questions - VNA & TDR measurements to support model correlation efforts and improve confidence in design stage What we need to see: - MS/BS in EE or equivalent experience - Minimum 1+ years of experience as a SI/PI engineer - Deep understanding of electromagnetic, specifically electromagnetic waves including transmission line theory and via properties - Proficient with HFSS, Sigrity, Hspice, and/or other simulation tools - Experienced with Cadence Allegro PCB designer and Constraints Manager - Understanding of high volume manufacturing variations and impact to channel signal integrity - Exposure to lab measurements including VNA & TDR experience - Passionate about SI/PI work - Good written & verbal interpersonal skills in English Ways to stand out from the crowd: - Familiarity with NRZ/PAM-4 signaling schemes - Exposure to interface timing budgets and system modeling - Familiarity with high-speed I/O design concepts including clock generation, transmitter & receiver design, and equalization schemes - PDN analyses including model generation and time domain simulation - Experience w/ Matlab, Python, and C as well as exposure to package design
Senior Deep Learning Research Engineer, LLM Infere...
We are seeking a Deep Learning Research Engineer to join our team and help develop the next generation of Large Language Model (LLM) inference algorithms. You will work on technologies that directly enhance NVIDIA's software, making the latest LLMs more efficient and accessible to users worldwide. This role is designed for someone with strong research foundations who also wants to build software that runs and scales into production systems across the world. By joining us, you will be part of a strategic effort to establish NVIDIA as the definitive platform for high-performance LLM inference. The work requires a combination of research taste, experimental rigor, and engineering ownership: you will explore new ideas, run rigorous evaluations, and help transform successful approaches into tools and implementations. What you'll be doing: - Develop and improve benchmarks, profiling workflows, and evaluation pipelines that make inference performance measurable and reproducible. - Design and lead the development of experimental frameworks that enable rapid, reproducible evaluation of algorithmic tradeoffs across quality, latency, throughput, and more. - Prototype new algorithms for LLM inference to advance the state of the art in both low-latency and high-throughput scenarios, translating them into practical software solutions that directly impact NVIDIA's products and customers - Trace and profile the performance of new algorithms on NVIDIA’s latest hardware, identifying bottlenecks and opportunities for algorithmic optimizations. - Collaborate with internal research, engineering, and product teams across the globe to drive the development of advanced inference technologies. - Stay ahead of research in LLM inference, efficient generation, model architecture, inference engines, and translate relevant advances into practical solutions. What we need to see: - MSc in Computer Science, Electrical Engineering, or a closely related field; or equivalent experience in an industrial research role. - At least 5 years of proven experience in applied research, research engineering, or algorithm engineering. - Excellent software engineering skills, particularly in Python and deep learning frameworks like PyTorch. - Proven experience with High-Performance Computing (HPC) environments, including training or running inference on large-scale GPU clusters (tens to hundreds of GPUs). - Interest in the systems side of deep learning, including inference engines, benchmarking, profiling, GPU efficiency, memory behavior, and deployment constraints. - A strong problem-solving mentality and a proactive attitude, driven by the ambition to deliver solutions with real-world impact. Ways to stand out from the crowd: - At least one publication in a top-tier AI/ML conference (e.g., NeurIPS, ICLR, ICML). - Deep understanding of LLM architectures coupled with hands-on experience in training large-scale models. - Hands-on research experience in LLM inference optimization algorithms such as speculative decoding or parallelization strategies. - Deep familiarity and experience with popular LLM inference frameworks (e.g., vLLM, TensorRT-LLM). We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Senior Enterprise Solution Engineer
We are looking for an experienced system engineer, who will play a dual role on the NVIDIA Enterprise Experience (NVEX) team. An awesome candidate is highly technical who can triage customer software issues and resolve customer problems as well as someone who can develop key enhancements and tools for the DGX Platform Software, Container Orchestrators, Deep Learning containers, and potentially other Enterprise related system software. This individual should have proven grasp of platform and systems engineering who understands Linux internals, knowledge about servers and has the ability to resolve hardware and/or OS internal issues. If you have a real passion for technology, and you are interested in a role that you can make a difference in and contribute at all different levels, this may be a phenomenal position for you. What you'll be doing: - Develop features and tools as part of solution engineering efforts to support all Enterprise Service offerings including, but not limited to DGX, NVAIE, Container Orchestrators (such as Kubernetes), GPU accelerated applications, and Deep Learning frameworks. - Work with NVIDIA Enterprise customers and internal users to improve the availability, reliability, and overall experience of working with NVIDIA Deep Learning Framework containers on NVIDIA GPUs. - Take ownership and drive customer issues on containers, Deep Learning frameworks, and Cloud deployment from inception to resolution. - Build upon the opportunity to research new use cases with GPUs for emerging container technologies and Deep Learning frameworks. - Bring independent analysis, communication, and problem-solving to customer experience. - Be on call one weekend per month in the event a customer has a Sev1 outage and requires engineering assistance. What we need to see: - BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience). - At least 5 years system software development and troubleshooting experience, ideally with some customer facing. - Intellectual curiosity, positive attitude, flexibility, analytical ability, self-motivation, and team-oriented. - Strong computer science concepts and excellent knowledge of Python and scripting methodologies. - Deep understanding of at least two of the following: data centers, servers, distributed systems, virtualization, deep learning frameworks, containers/containerization (ie Docker, Kubernetes), hybrid cloud (ie AWS, GCP). - You'd have cultivated a deep Linux knowledge, and be very comfortable working in various Linux environments as well as with Windows OS’s. - Professional-level communication skills, interpersonal skills with a passion to solve problems. Ways to stand out from the crowd: - Proven experience in developing, triaging and debugging on Linux and Containers and deep learning frameworks. - Experience working with distributed systems especially container orchestrators. - Any exposure to system level debug and triaging experience. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are expanding fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you.
Data Center Infrastructure Specialist
NVIDIA is looking for a Data Center Deployment Specialist to join its Professional Services team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest data centers in the world! NVIDIA is looking for someone with the ability to work on a dynamic customer-focused team that requires excellent interpersonal skills. As a Data Center Infrastructure Specialist, you will be interacting with customers, partners, and internal teams, to analyse, define and implement large scale Datacenter projects. The scope of these efforts includes a combination of Datacenter Infrastructure design and cluster deployment planning. What you will be doing: - Design and implement flawless data center infrastructure solutions to meet the needs of our customers. - Collaborate with cross-functional teams to ensure the successful deployment of data center infrastructure. - Datacenter Planning: Floor Plan, Rack Elevation, Simulation - Cable deployment planning including - ensuring requirements are accurate such as number and type of connections, port assignments, and timing of activity while following standard methodologies, Point-to-Point Design. - Deploy and Support NVIDIA products. - Validating and updating all related work instructions for Datacenter activities. - Responsible for providing input for Data Center Standards updates as required; balancing multiple activities and priorities; participate in projects calls. - Documenting processes and keeping event logs. - Escort and oversee on-site work delivered by partners and third-party vendors. What we need to see: - 5+ years of proven experience as a data center infrastructure engineer, field service engineer or similar with background in designing and implementing data center infrastructures. - Bachelor's degree or equivalent experience in a relevant field. - In-depth knowledge of data center environments, servers, and network equipment. - Extensive experience in installing, monitoring, and maintaining data center equipment. - Solid understanding of networking, storage, and virtualization technologies. - Excellent problem-solving skills and attention to detail. - Ability to work as part of a team, in a fast and highly dynamic environment. - Exceptional communication and interpersonal skills. - Proficiency in documenting processes. - Willingness to travel. Way to stand out from the crowd: - Network certification such as: Cisco Certified Network Associate (CCNA), Juniper Networks Certified Associate - Junos (JNCIA-Junos) - Knowledge with InfiniBand Technology - Collaboration with R&D and network engineering teams. - Outstanding interpersonal skill. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world, working for us. Our commitment to pushing boundaries and delivering exceptional solutions is unparalleled. As a Data Center Infrastructure Specialist, you will play a key role in shaping the future of computing and driving the success of our clients. At NVIDIA, we are an equal opportunity employer. We value diversity and are committed to creating an inclusive and supportive work environment for all employees. If you are a proactive and driven individual, creative with a strong interest in current technology trends, this is the opportunity you have been waiting for. Join us at NVIDIA and be part of our journey to shape the future of computing. Apply now and let's work together to make a difference!
Senior Solution Architect, Cloud Infrastructure -...
NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems. NVIDIA is looking for Senior Cloud Infrastructure/DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What You'll Be Doing: - Develop and maintain continuous integration and delivery pipelines . - Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources. - Deploy monitoring solutions for the servers, network and storage. - Perform troubleshooting bottom up from bare metal, operating system, software stack and application level. - Being a technical resource, develop, re-define and document standard methodologies to share with internal teams Support Research & Development activities and engage in POCs/POVs for future improvements . What We Need To See: - BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture. - 5+ Years of Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting Manage Linux job/workload schedulers and orchestration tools. - Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software. - Direct design, implementation and management experience with cloud computing platforms (e.g. AWS, Azure, Google Cloud). - Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes and Singularity. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies. - Python programming and bash scripting experience. - Comfortable with automation and configuration management tools including Jenkins, Ansible, Puppet/Chef, etc. - Deep knowledge of Networking Protocols like InfiniBand, Ethernet Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix). - Strong written, verbal, and listening skills in English are critical. Ways To Stand Out From The Crowd: - Knowledge of CPU and/or GPU architecture . - Knowledge of Kubernetes, container related microservice technologies. - Experience with GPU-focused hardware/software (DGX, CUDA.) - Background with RDMA (InfiniBand or RoCE) fabrics. 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 individuals in the world working for us. If you're creative and autonomous, we want to hear from you.
Senior Solution Architect, Cloud Infrastructure-De...
NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems. NVIDIA is looking for Senior Cloud Infrastructure/DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What You'll Be Doing: - Develop and maintain continuous integration and delivery pipelines . - Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources. - Deploy monitoring solutions for the servers, network and storage. - Perform troubleshooting bottom up from bare metal, operating system, software stack and application level. - Being a technical resource, develop, re-define and document standard methodologies to share with internal teams Support Research & Development activities and engage in POCs/POVs for future improvements . What We Need To See: - BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture. - 5+ Years of Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting Manage Linux job/workload schedulers and orchestration tools. - Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software. - Direct design, implementation and management experience with cloud computing platforms (e.g. AWS, Azure, Google Cloud). Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes and Singularity. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies. - Python programming and bash scripting experience. Comfortable with automation and configuration management tools including Jenkins, Ansible, Puppet/Chef, etc. - Deep knowledge of Networking Protocols like InfiniBand, Ethernet Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix). - Strong written, verbal, and listening skills in English are critical. Ways To Stand Out From The Crowd: - Knowledge of CPU and/or GPU architecture . - Knowledge of Kubernetes, container related microservice technologies. - Experience with GPU-focused hardware/software (DGX, CUDA.) - Background with RDMA (InfiniBand or RoCE) fabrics. 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 individuals in the world working for us. If you're creative and autonomous, we want to hear from you.
Senior Solutions Architect, AI Hyperscalers
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 extraordinary technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. NVIDIA is searching for an AI/ML Solutions Architect focusing on Hyperscale customers and Cloud Service Providers. Your primary responsibilities will be to lead software customer technical engagement for AI training, inference and infrastructure being deployed at vast scale. You will work across multiple organizations within NVIDIA as well as at the customer to ensure successful and trouble-free deployments. If you would you like to partner with a large company to build automation and management to create a robust large scale artificial intelligence infrastructure and are interested in the optimization and characterization of customer specific AI models and pipelines - you should apply! What you’ll be doing: - As a key technical member of a focused account team, you will serve as the main point of contact for NVIDIA products, enabling internet giants and cloud providers to have an innovative AI/ML software infrastructure. - Work directly with best-in-class engineering teams to secure design wins, address challenges, bring solutions to production, and support them throughout their lifecycle. - Become a trusted advisor to your customer by understanding their environment, constraints, and long-term strategy. Translate these insights into product requirements and innovative solutions. - Help your customer enhance the value of NVIDIA technology, and provide feedback to NVIDIA for future product improvements. - Facilitate the resolution of customer issues, offering timely and proactive communications to mitigate risks. - Lead workshops, demos, and proof-of-concepts to showcase NVIDIA’s AI/ML capabilities. - Guide customers on standard processes for scalable AI model deployment and inference optimization. What we need to see: - Minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience. - 8+ years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions. - Proven understanding of Linux, including solving, optimization, and customization for AI/ML workloads. - Strong understanding of data science and machine learning infrastructure—software and hardware. - Professional-level communication skills, including the ability to tailor messages for varying technical audiences and maintain composure in high-pressure situations. - Excellent follow-up and interpersonal skills, with a true passion for problem-solving. - Proficient in Python, with the ability to develop scripts and build custom tools. Experience with parallel programming or GPU acceleration (e.g., CUDA) is helpful. - Shown eagerness to learn and apply new technologies. Ways to stand out from the crowd: - Experience with Chatbots, RAG pipelines, vector databases, and distributed training or inference workloads. - Experience or background in HPC (High Performance Computing) environments for AI or ML applications. - Familiarity with multi-node GPU clusters and performance tuning for large-scale AI workloads. - Experience developing in cloud and/or virtualized environments, containerized solutions, with knowledge of Docker, Kubernetes - Background with common deep learning frameworks such as PyTorch or JAX. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 17, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Principal Software Engineer - Compute Infrastructu...
NVIDIA has been reinventing computer graphics, PC gaming, and accelerated computing for 30 years. It is 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, generative AI, 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. We are seeking a highly skilled Principal Software Engineer to jo in our dynamic team. Our company is at the forefront of technological innovation, and we are dedicated to drivin g efficiency, defi ning platform architecture, and optimizing the performance of our infrastructure both on-prem and in the cloud. You will lead the architectural vision for a massive global platform and spearhead the operationalization of our internal frontier-class AI inference syste ms. Join us in this exciting endeavor! What You Will Be Doing: - Define Platform Architecture: Lead initiatives to architect and transform our global enterprise compute platform—running thousands of nodes and tens of thousands of VMs and containers via OpenShift and KubeVirt—by defining service tiers, SLAs, and automated cluster lifecycles. - Operationalize Frontier AI Infrastructure: Build the operational foundation for our internal AI inference platform scaling to frontier-class models. You will develop automated remediation pipelines, hardware watchdogs, and telemetry for pre-release, rack-scale GPU systems (including Blackwell and upcoming architectures). - Drive Strategic Capacity & Scale: Collect and review system data for capacity planning to navigate extreme hardware supply constraints. Develop proactive strategies, including public cloud bursting, hardware dogfooding, and evaluating alternative compute architectures (e.g., ARM). - Build the "Paved Road": Collaborate with highly autonomous NVIDIA engineering teams to drive cultural adoption of standard platforms. You will design compelling self-service architectures, APIs, and Terraform/OpenTofu providers that teams want to use. - Lead Complex Migrations: Evaluate existing application architectures and drive the fraught but critical migration of massive legacy workloads—including large-scale, long-running VDI environments—into modern Kubernetes orchestration. What We Need To See: - Bachelor’s degree in Engineering, Computer Science, Mathematics, or related field, or equivalent experience. - 15+ years of proven experience in compute platform engineering, site reliability, or systems architecture with a heavy focus on automation at massive scale. - Deep expertise in Kubernetes architecture and designing/deploying virtualization architectures, specifically operating VMs inside K8s (KubeVirt, OpenShift). - In-depth knowledge of hardware technologies (GPUs, high-speed backplane networking) with a track record of mitigating hardware-level failures, silent data corruption, and anomalies in large-scale environments. - Experience running large global environments spanning bare metal, virtualized infrastructure, and cloud with a unified GitOps posture (ArgoCD or similar). - Proficiency in programming languages such as Go and/or Python, alongside expert-level infrastructure-as-code development (Terraform, Config Management). - Strong leadership skills with the ability to influence technical direction across highly autonomous teams without relying on top-down mandates. Ways To Stand Out From The Crowd: - Hands-on experience managing bleeding-edge, pre-release hardware in production environments. - Deep understanding of advanced storage migrations and protocols (NFSv4, NVMe/TCP, Hyperconverged storage). - Solid understanding of microservices architecture and seamless multi-cloud deployment strategies (AWS, GCP). - Proven track record of building "Day 2" operational maturity (self-service, advanced auto-remediation, strict SLAs) from the ground up on existing foundations. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you are creative and autonomous, we want to hear from you! LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 391,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 17, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
AI Researcher, TAO Multi-Modal Model Development
NVIDIA is seeking a motivated AI Model Development Researcher to join the TAO — Train, Adapt, Optimize — Multi-Modal Model Development team in Hanoi or Ho Chi Minh City, Vietnam. In this role, you will contribute to the development, adaptation, optimization, and evaluation of advanced AI models within the NVIDIA frameworks. You will work on cutting-edge areas such as multi-modal learning, vision-language models, image segmentation, foundation model adaptation, and scalable deep learning workflows. You will collaborate with engineers, researchers, and cross-functional teams to build practical AI solutions that can be integrated into production pipelines, NVIDIA SDKs, and real-world customer use cases. This is an excellent opportunity for an early-career engineer/scientist who is passionate about machine learning, deep learning, vision-language models, and building high-quality AI software. What you'll be doing: - Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks. - Contributes to the design and implementation of vision-language models (VLMs) and universal segmentation systems. - Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability. - Collaborate with cross-functional teams to integrate your research into production-level pipelines and NVIDIA SDKs. - Participate in research discussions, code reviews, and technical documentation to share insights and improve methodologies. What we need to see: - BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or a related field (or equivalent experience). - 2+ years of experience in machine learning, deep learning, or computer vision model development. - Strong Python programming skills and proficiency with PyTorch or similar frameworks. - Solid understanding of neural network architectures, transformers, and multi-modal learning techniques. - Excellent problem-solving abilities, attention to detail, and a collaborative mindset. - Familiarity with vision-language models, image segmentation, or large-scale pretraining is a strong plus. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Physical Design Engineer
We are now looking for a Senior Physical Design Engineer. 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 tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice to join our diverse team today. What you'll be doing: - Responsible for all aspects of physical design and implementation of GPU and other ASICs targeted at the desktop, laptop, workstation, and mobile markets. - As a member of a team, we will all participate in establishing physical design methodologies, flow automation, chip floorplan, power/clock distribution, chip assembly and P&R, timing closure. - Craft designs for static timing analysis, power and noise analysis and back-end verification. What we need to see: - BSEE (MSEE preferred) or equivalent experience. - 8+ years of experience in large VLSI physical design implementation on 5nm, 4nm and 3nm technology. - Your successful track record of delivering designs to production is a requirement. - Shown experience in the following areas: Power, Performance and Area improvement Initiatives is a plus. - Already a validated strong power user of P&R, Timing analysis, Physical Verification and IR Drop Analysis CAD tools from Synopsys (ICC2/DC/PT/STAR-RC/ICV),Cadence (Innovus, Tempus, SeaHawk ) and Mentor Graphics. - Deep understanding of custom macro blocks such as RAMs, CAMs, high-speed IO drivers, PLLs. - Confirmed prior experience in timing closure, clock/power distribution and analysis, RC extraction and correlation, place/ route and tapeout solutions. - To be successful you should possess strong analytical and debugging skills required. - Proficiency using Python, Perl, Tcl, Make scripting is helpful. NVIDIA is widely considered to be the leader of AI computing, and 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. If you're creative and autonomous, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Manager, PCIe Firmware - Physical Layer
At NVIDIA, our work powers accelerated computing and modern AI — from scientific research to the generative AI applications reshaping our world. The PCIe physical layer is where firmware meets the silicon: link bring-up, signal integrity, and cross-generation behavior on real silicon and in real customer environments. NVIDIA is building a dedicated Physical Layer team within its PCIe Firmware organization, with ownership across the networking product portfolio — and we are looking for a hands-on first-line manager to lead it! What you'll be doing: - Lead a focused team of physical layer firmware engineers as a player-coach — guiding debug directly while growing the team's engineers and tech leads. - Own the team's delivery for PCIe link bring-up, equalization, recovery, and physical-layer-related customer escalations across multiple products. - Partner with Chip Design, Architecture, Software, Validation, and Customer Engineering to drive issues to root cause and turn point fixes into reusable improvements. - Act as the technical reference on physical layer scope — both for triage and for cleanly identifying when an issue is not physical layer. - Champion AI-native engineering inside the team and across the organization, applying AI tools to triage, debug, and knowledge capture. What we need to see: - Degree in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience. - 8+ overall years of engineering experience, with 3+ years in engineering management or equivalent tech lead experience on a path into management. - Strong PCIe foundation: link training, equalization, recovery flows, and cross-generation behavior. - A track record of personally driving hard link issues to root cause, working from state traces and eye diagrams alongside silicon and signal integrity engineers. - Proven ability to grow engineers, run a delivery cadence, and make prioritization calls under constraint. - An active operator: when execution is blocked, you step in. - Clear communicator across engineers, partners, and customers. Ways to stand out of the crowd: - Hands-on PCIe link bring-up on real silicon, signal integrity work, lane margining, or cross-generation interop. - Direct experience with high-speed SerDes behavior, thermal-sensitive link issues, or customer-facing escalation work. - Practical use of AI/ML tools in engineering — pattern matching across logs, summarizing state machine traces, building shared knowledge bases. - Familiarity with networking products, Linux, and scripting in Python. - Experience operating across HW/FW/SW boundaries. This is a chance to build and lead a new team with direct ownership of a critical technical surface across NVIDIA's networking portfolio. If that fits you — apply! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. We are committed to making reasonable accommodations for qualified individuals with disabilities. If you need assistance or accommodation during the application process, please contact us.
Senior Software Engineer, AI Networking
NVIDIA seeks a senior software engineer to join the AI Networking co-design and benchmark R&D team. In this pivotal role, the candidate is responsible for building and productizing machine learning tools. These include tools that use ML-based combinatorial optimization and build space exploration (DSE) techniques. These tools will be employed to optimize AI workloads across large GPU and CPU clusters, thereby ensuring the most efficient and productive utilization of system resources at data center scale. The role involves working on distributed Deep Learning, particularly within LLM training and inference stacks. A strong passion for collective communication and networking is desirable. The candidate will interact with diverse hardware and platforms, such as Host Channel Adapters (HCAs), Switches, CPUs, GPUs, and complete Systems. Furthermore, the role requires engagement across multiple software layers, including LLM applications, machine learning frameworks, and communication and computing libraries. The candidate will develop tools and methodologies using Machine Learning (ML) for comprehensive performance analysis and optimization, potentially incorporating learning-based agentic techniques. This work involves deep-diving across the software stack, from LLM applications and ML frameworks down to communication and computing libraries. This position offers a distinct opportunity to support the core infrastructure powering the next generation of large-scale AI systems. What you'll be doing: - Design and implement resource allocation and combinatorial optimization techniques (e.g., reinforcement learning, LLM agents for DSE, Bayesian optimization and other multi-objective optimization techniques) to optimize LLM models at datacenter scale. - Research, develop, and deploy AI/ML techniques to optimize large-scale Deep Learning (LLM) training and inference on NVIDIA supercomputers and distributed systems. This includes a focus on high-performance networking and NVIDIA communication libraries. - Build and productionize ML-based tools for performance prediction and optimization, with a strong emphasis on networking aspects. - Develop and deploy a scalable, reliable data curation pipeline capable of handling complex data types, such as time series and PyTorch model graphs, to effectively support the training of high-performance Machine Learning models. - Collaborate across hardware and software teams to deliver valuable performance analysis insights. - Lead performance test planning, establish performance targets for new technologies and solutions, and drive efforts to achieve those performance goals. What we need to see: - PhD or Master's degree in Computer Science, Software Engineering, or equivalent experience. - 4+ years of experience applying machine learning techniques to computer architecture and system optimization problems. Desired experience involves bringing to bear ML at the intersection of at least two of the following areas: HPC, networking, and AI applications. - Hands-on experience developing and deploying various learning algorithms (e.g., reinforcement learning, offline RL, supervised learning) to tackle optimization challenges within computer architecture, system design, or networking domains. - Proficiency in building and using ML models with leading frameworks such as PyTorch or TensorFlow, or JAX. - Proven ability to apply GNNs/transformers-based optimization to PyTorch model graph and Kineto execution traces. - Expertise combining knowledge of NVIDIA GPUs, the CUDA library, and deep learning frameworks (TensorFlow/PyTorch) with networking concepts, including collective communication libraries (like NCCL) and protocols (such as RoCE and RDMA). - Strong programming capabilities in Python, Bash, and C++. - A collaborative teammate with effective communication and interpersonal abilities. Ways to stand out from the crowd: - In-depth knowledge and experience with machine learning/reinforcement learning and frameworks. - Comprehensive understanding of computer architecture, system architecture and networking. - Extensive experience in applying machine learning techniques such as GNNs or related graph-based models. - Knowledge in PyTorch, CUDA, and NCCL libraries. - Proven software engineering/development skills With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward‑thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large‑scale, high‑impact data platforms, we’d love to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Deep Learning Engineering - Autonomous Vehi...
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. At NVIDIA, we’re building the future of autonomous driving — from the silicon to the full-stack AI systems that power next-generation robots on wheels. Our ability to deliver safe, scalable autonomy depends on one thing above all: Data. Extensive, diverse, high-quality data. We are seeking a highly skilled Deep Learning Engineer to develop systems and algorithms extracting intelligence from petascale fleets. This role offers an opportunity to build the data engine powering one of the world’s most advanced AI platforms. We are looking for hands-on experience training and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments. You will collaborate with other researchers, software engineers to bring pioneering AI models from prototype to production. What you will be doing: - Explore SOTA LLM/VLM models for search and classification of AV scenarios - Hands on model developments such as fine-tuning large LLM/VLMs for internal use cases - Collaborate with software engineers and researchers to ensure seamless integration of models from training to deployment. What we want to see: - Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience) - 10+ years of professional experience in deep learning or applied machine learning. - Strong foundation in deep learning algorithms, including hands-on experience with LLMs and VLMs - Deep understanding of general transformer architectures, inference bottlenecks, and popular model architectures such Qwen family. - Proficient in building and deploying models using PyTorch in production-grade environments. - Solid programming skills in Python Ways to stand out from the crowd: - Proven experience deploying LLMs or VLMs at scale in real-world applications using vLLM, SGLang. - Hands-on experience with SFT, DPO, GRPO techniques for fine-tuning - Proven experience in developing image and video search solutions at scale. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Developer Advocate – Reinforcement Learning
The NVIDIA developer marketing group is looking for a developer advocate who is passionate about working with innovative technology, building well-documented inspirational demos, and sharing that code with the AI community. Our team is deeply committed to championing the developer ecosystem that builds applications on NVIDIA’s platform. We need a candidate who understands developers and works with the developer marketing on launching new technology. Do you have the rare blend of both engineering and marketing skills? We need hard-working and creative people who are passionate about teaching our developer community how to employ accelerated computing. If you aspire to this calling, we would love to learn more about you! What you'll be doing: - Create impactful and relevant content (e.g., demos, blogs, presentations, videos, etc.) and engage with developers, researchers, and students at events online or in person. - Collaborate with the product marketing team to launch emerging technology, write code, and share it with the community to inspire developers. - Actively participate on public-facing NVIDIA channels, including forums, Discord, and social media, helping developers understand our demos and encouraging them to build their own applications. - Some travel may be required to present at trade shows and conferences. What we need to see: - Bachelor's degree in Computer Science or related field (or equivalent experience). - 5+ years of relevant experience, including 3 years of engineering experience (or equivalent). - World-class communication and presentation skills with a proven track record of articulating the value proposition of an emerging technology. - Experience presenting to technical audiences and writing developer-facing content. You will be asked to provide samples of prior work. - Ability to design and implement Reinforcement learning and post-training pipelines for LLM to improve model reasoning, safety, and instruction-following capabilities. - Strong programming skills with the ability to develop easy-to-understand examples on training pipeline using AI frameworks such as PyTorch, JAX, and NeMo-RL - Ability to prioritize and work through constantly evolving projects that strive to demonstrate the benefits of new, potentially unstable technology. Ways to stand out from the crowd: - In-depth knowledge of software architecture, system design, and application development. - Hands-on experience popular reinforcement learning libraries such as Unsloth, TRL, OpenRLHF. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Platform AI Engineer - Silicon Co-Design Gr...
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's Silicon Co-Design Group (SCG) is seeking Senior AI Platform Engineers to set the technical direction and own end-to-end delivery of the AI-driven efficiency platform powering our intelligent automation ecosystem. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production — over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we need the engineer who defines the architecture everyone else builds on. In this role, you will set the platform strategy, own the full lifecycle of a production AI infrastructure, and drive alignment across multiple engineering departments — with personal accountability for its reliability, scalability, and long-term evolution. If you are energized by building foundational platforms at the intersection of ML infrastructure and large-scale systems, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed! What you'll be doing: - Leading technical strategy and roadmap for the AI-driven efficiency platform to meet SCG cross-functional use cases, investment areas and priority: defining architectural direction, making infrastructure investment decisions, and aligning roadmap priorities across silicon design, methodology, validation, and applied AI teams. - Partnering with domain agent builders across SCG teams and functional domains to define platform contracts and onboard new agents and skills. - Owning end-to-end delivery of the platform — from design and implementation through sustained production operation — with accountability for security, reliability, performance, and evolution. - Driving platform-wide decisions with cross-functional impact and leading the unified solutions: orchestration patterns, authentication and authorization, observability and SLA enforcement, and storage and caching strategies that scale across heterogeneous compute environments. - Serving as the technical authority for AI-driven infrastructure across SCG: setting engineering standards, resolving cross-team architectural conflicts, and mentoring senior engineers. - Identifying gaps and opportunities at the frontier of AI-driven infrastructure tooling — evaluating emerging technologies, shaping internal standards, and contributing learnings back to SCG engineering organization. What we need to see: - BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 12+ years of hands-on experience designing and operating production-grade platform or backend infrastructure. - 5+ years of direct ML infrastructure experience, including end-to-end ownership of a model serving platform or latency-sensitive backend service from initial architecture through sustained production operation. - Demonstrated track record of setting technical direction at the department or company level: defining platform strategy, establishing architectural standards, and leading initiatives spanning multiple teams. - Strong Python skills and proficiency in at least one compiled language such as C, C++, Go, Java, or Rust. - Hands-on experience with job queues + sandboxed execution (Kubernetes Jobs, Celery/Sidekiq/Temporal, container runtimes with resource isolation). - Proven ability to own high-stakes systems with rigorous operational discipline: structured observability, graceful degradation, clearly defined SLOs, and a sustained track record of reliability under pressure. - Strong communication and leadership skills, with the ability to align senior stakeholders and drive architectural decisions across organizations with competing priorities. Ways to stand out from the crowd: - Industry recognition in ML infrastructure or distributed systems — through publications, conference talks, open-source contributions, or technical leadership visible beyond your current organization. - Experience driving platform architecture at company scale, including engineering standards or frameworks broadly adopted by other teams. - Exposure to silicon design, methodology, validation or EDA toolchains, especially the cadence of chip development lifecycles. - Experience building or operating AI platforms within a silicon development, validation or EDA environment, with firsthand understanding of the reliability and scale demands of chip design toolchains. - Track record of mentoring senior engineers and growing technical talent — shaping the capabilities of the team as much as the platform itself. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family ( www.nvidiabenefits.com ).
Senior Perception Engineer, Obstacle Foundation Mo...
Intelligent machines powered by artificial intelligence—computers that can learn, reason, and interact with people—are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence. They act as the brain of computers, robots, and self-driving cars. These machines can perceive and interpret their surroundings. We are seeking an exceptional Senior Perception Engineer to help design and productize NVIDIA’s next-generation autonomous driving perception stack. You will work on the core 3D obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, multi-modal, and vision-language techniques where they add real value. What you'll be doing: - Develop and improve the technical build, architecture, and roadmap for 3D obstacle perception to support end-to-end autonomous driving. Use innovative CNN and transformer-based architectures when appropriate. - Design and implement advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion (camera, radar, lidar) for obstacle detection and tracking, including opportunities to explore BEV and transformer-based 3D perception. - Build efficient, production-grade deep learning models by defining objectives with the team. Select and prototype architectures, run experiments, and follow training and evaluation guidelines. Use techniques like large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA). - Help define and maintain KPI frameworks to quantify perception performance; analyze large-scale real and synthetic datasets to identify failure modes and systematically improve accuracy, robustness, and efficiency, incorporating approaches like self-supervised and representation learning when beneficial. - Contribute to the data strategy for perception by specifying data and labeling requirements. Help prioritize data collection and annotation. Collaborate with data and ground-truth teams, including model-assisted workflows such as active learning, auto-labeling, and multimodal AI systems combining vision and language. Also work with model-in-the-loop tooling. - Collaborate with safety, systems, and software teams to ensure perception solutions meet product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale. What we need to see: - PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. - Hands-on experience developing deep learning–based perception or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production. - Proven experience in data-driven development, including close collaboration with data, labeling, and validation teams on data strategy, labeling quality, and iterative model improvement. - Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software. - Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams. Ways to stand out from the crowd: - Experience designing and deploying perception solutions for autonomous driving or robotics using camera-based deep learning at scale. - Hands-on experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms. This includes optimizing for latency, memory, and compute constraints. Experience with modern architectures such as CNNs and transformers is required. Familiarity with methods such as extensive pretraining, efficient tuning of parameters (e.g., LoRA), or vision-language models (VLMs) is also needed. - Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems at leading conferences/journals (e.g., CVPR, ICCV, NeurIPS, IROS). - Deep understanding of 3D computer vision fundamentals, including camera modeling and calibration (intrinsic and extrinsic), multi-view geometry, and 3D representations, ideally with experience applying these concepts in transformer-based 3D or BEV perception pipelines. - Experience with CUDA development and optimizing training or inference pipelines through custom CUDA kernels or other GPU-accelerated components.
Principal CPU Power Architect
Do you want to help drive the development of CPU technology for architectures used for artificial intelligence (AI), agentic workloads, deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming, virtual reality, and autonomous vehicles? Come join the CPU architecture team and help us the boundaries for all our CPU products! What you'll be doing: - Bridge the gap between architecture, RTL implementation, and physical design. - Serve as subject matter expert on power delivery/regulators, power gating, di/dt, and thermal throttling. - Analyze power trade-offs for different die stacking and packaging proposals. - Propose and drive improvements related to power and power methodology for our custom CPU cores. What we need to see: - BS/MS in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience. - 15 or more years of relevant experience. - Extensive background in CPU architecture. - Solid understanding of power consumption, and power efficiency concepts. - Experience of RTL development. - Detailed understanding of process technologies and circuit design. - Well versed in low power techniques that span the entire stack from SW, Architecture, RTL, VLSI, and process. Ways to stand out from the crowd: - PhD or research experience. - Advanced knowledge in the area of physical design. - Knowledge of GPU and SOC design. - Experience of advanced packaging technologies. - Strong communication skills. NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. Our technologies power transformative applications across industries — from robotics and autonomous vehicles to healthcare and climate research. With the introduction of the Grace CPU Superchip, and more recently, the announcement of the Vera CPU, NVIDIA has expanded into the CPU server market, complementing our world-class GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency. The CPU architecture team is driving innovations that integrate seamlessly with NVIDIA’s broader technology stack, enabling faster AI model training, agentic use-cases, efficient data processing, and scalable cloud deployments. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 19, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Compiler Engineer - AI
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 an AI Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate brings broad experience across machine learning, including reinforcement learning, genetic/evolutionary algorithms, predictive modeling, complex systems, and high-dimensional data analysis, along with strong foundations in compiler design and domain-specific languages. This role is focused on building AI-driven compiler intelligence for production compiler pipelines, delivering measurable improvements in performance and efficiency, and advancing LLM-enabled workflows for compiler decisioning and developer productivity. What you'll be doing: - Join a team driving innovative solutions in compilers and developer tools through applied machine learning and AI. - Collaborate with world-class engineers to shape next-generation compiler capabilities that power large-scale, high-impact products. - Design and implement end-to-end compiler optimization workflows, from feature engineering and model development to compiler integration and production rollout. - Develop and integrate learning-based decision systems into compiler passes, code generation flows, and optimization pipelines. - Build robust interfaces between LLM systems and compiler infrastructure for optimization recommendations, decision support, and workflow automation. - Partner with compiler, architecture, and performance teams to validate impact on representative workloads and benchmark suites. - Lead experimentation, evaluation, and deployment with strong standards for reliability, scalability, and performance. What we need to see: - BS/MS/PhD in Computer Science or a related field (or equivalent experience), with a focus on machine learning and compiler/developer tools. - 8+ years of software engineering and AI/ML experience, preferably in tools or systems development. - Strong knowledge of compilers, code generation, and GPU architecture. - Demonstrated proficiency in Python and C/C++. - Strong mathematical and scientific foundation relevant to AI/ML and compiler technologies. - Hands-on experience with LLVM/MLIR-based compiler development, including optimization passes, code generation, or frontend integration. - Experience building or integrating LLM-based systems, agents, or developer tooling in production environments. Ways to Stand Out From the Crowd - Deep familiarity with reinforcement learning, genetic/evolutionary algorithms, predictive modeling, and complex systems. - Proven track record of deploying AI/ML solutions in production and embedded environments. - Strong experience integrating LLMs into systems workflows with attention to reliability, latency, and evaluation quality. - Demonstrated measurable outcomes such as runtime gains, compile-time improvements, or efficiency improvements on real-world workloads. - Publications, open-source contributions, or patents in compilers, AI/ML systems, or performance engineering. With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous program manager with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 19, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. deeplearning
Senior Data Center Network Deployment Engineer
NVIDIA is looking for a Data Center Network Deployment Engineer to join the Networking clusters solutions HPC/AI Infrastructure team. We are building supercomputers and AI clusters based on groundbreaking technologies. We are looking for a network/system engineer to be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing. You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. Does this sound like you? If so, we would love to hear from you! What you'll be doing: - Deploy, manage and maintain large scale AI Data Centers - control, network and storage stack - Work with multiple software and hardware teams to optimize the clusters networking health and performance - Develop and implement automation scripts for network, compute and storage operations and deployments - Supporting Research & Development activities and engaging in POCs/POVs for future improvements What we need to see: - B.Sc. in Engineering or CCNP certificate - 8+ years of proficiency in networking fundamentals, configuring ethernet switches, understanding the TCP/IP stack, and data center architecture. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalls, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. - Proactive individual with the ability to work independently, prioritizing tasks to optimize technology and enhance customer experience. - Provides ad-hoc knowledge transfers, develops handover materials, and offers deployment support for engagements. Ways to stand out from the crowd: - Combination of interpersonal skills and technical competence - Knowledge of HPC and AI solution technologies from CPUs and GPUs to high speed interconnects and supporting software - Experience with multiple storage solutions such as Lustre, GPFS, and newer and emerging storage technologies. - Automation tooling background (Ansible, Salt, Puppet 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 individuals in the world working for us. If you're creative and autonomous, we want to hear from you! LI-Hybrid
Senior HPC DevOps Engineer
NVIDIA is looking for an experienced HPC DevOps and Network Engineer to help us build the supercomputers and HPC clusters of the future. As a Senior HPC DevOps Engineer, you'll be a key player in groundbreaking advancements in artificial intelligence and GPU computing. Your expertise will drive the latest breakthroughs, providing insights on at-scale system design and tuning mechanisms for large-scale compute runs. You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. What you’ll be doing: - Innovate and Implement: Design, implement, and maintain large-scale HPC/AI clusters with state-of-the-art monitoring, logging, and alerting systems. - Infrastructure as Code (IaC): Utilize and develop tools to manage infrastructure as code, ensuring scalable and repeatable deployments. - Streamline CI/CD Pipelines: Develop and maintain continuous integration and continuous delivery (CI/CD) pipelines to automate and streamline deployment processes. - Automate Everything: Develop automation scripts and tools to automate deployment, configuration management, and operational monitoring. - Develop complex Networking automations. - Troubleshoot Complex Issues: Perform comprehensive troubleshooting from bare metal to application level, ensuring system reliability and efficiency. - Lead and Educate: Serve as a technical resource, developing and sharing best practices with internal teams. - Drive Innovation: Support R&D activities and engage in proof of concepts (POCs) and proof of values (POVs) for future improvements. What we need to see: - B.Sc. in Computer Science, Engineering, or a related field with 5+ years of experience. - Deep knowledge of HPC and AI solution technologies, including CPUs, GPUs, high-speed interconnects, and supporting software. - Advanced proficiency in programming and scripting languages, with a solid understanding of object-oriented programming principles. - Familiarity with Jenkins, Ansible, Puppet/Chef. - Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu), networking and OS-level security. - Deep understanding of networking protocols such as InfiniBand and Ethernet. - Experience with job scheduling workloads and orchestration tools such as Slurm and Kubernetes. - Experience with multiple storage solutions like Lustre, GPFS, ZFS, and XFS. - Expertise with virtual systems (VMware, Hyper-V, KVM, Citrix). - Familiarity with cloud platforms (AWS, Azure, Google Cloud). Ways to stand out from the crowd: - Proven networking experience or strong knowledge through professional networking training. - Architectural Insight: Knowledge of CPU and/or GPU architecture. - Container Expertise: Understanding of Kubernetes and container-related microservice technologies. - GPU Focus: Experience with GPU-focused hardware/software (DGX, CUDA). - RDMA Fabrics: Background with RDMA (InfiniBand or RoCE) fabrics. At NVIDIA, we value diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We provide reasonable accommodations to ensure all individuals can participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Join us and be part of a team that's pushing the boundaries of technology and making a real impact in the world.
Applied AI Engineer, Product Convergence and Closu...
Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production. Over 200 product SKUs were optimized during the Blackwell generation alone! Now we're looking for an engineer to help us rebuild that toolchain around AI. We focus on the silicon layer of NVIDIA's productization work: the chip behavior piece. Our tools run the simulation, configuration, and data flow that take a chip's power, performance, and yield from pre-silicon estimates through to the values that ship in firmware and populate customer specs. This role is about making those tools talk to each other better, using AI to optimally move outputs from simulation into the downstream firmware, manufacturing, and specification systems that consume them. What you'll be doing: - Build the infrastructure that turns raw simulation data (power, noise, binning yields, and more) into real firmware tuning, product specs, and manufacturing limits. You own the pipelines between tools. - Use LLMs and agents across the toolchain to automate the analysis, validation, and reporting work that currently costs engineering countless hours per chip. - Build the observability and validation systems that catch data errors and inconsistencies before they turn into release blockers. - Work with product convergence, silicon architecture, firmware, and manufacturing teams to translate new hardware requirements and capabilities into workflows that make it to production. What we need to see: - BS/MS in CS, CE, EE, or Systems Engineering, or equivalent experience. - 4+ years shipping production Python services and data pipelines (FastAPI, async workflows, databases, modern web frontends). - Hands-on experience applying LLMs to engineering problems: agents, MCP, RAG, or evaluation pipelines. Have shipped an LLM-backed feature in production and can tell us about a time you had to debug one. - Strong instincts for data quality: the automated checks, schema validation, and integration tests that keep pipelines trustworthy when inputs change. - You keep up with a fast-paced AI landscape and can distinguish which new tools matter and which are just hype Ways to stand out from the crowd: - Silicon product proficiency (speed, power, voltage noise, binning); MCP, DSPy, or LLM evaluation frameworks; Perl interop for legacy chip-data workflows; have crafted dashboards and visualizations for diverse collaborators. Keeping up with every new feature and architectural change that NVIDIA packs into each chip generation is a real challenge. And because our users are directly on the path to production, support questions don't always wait for business hours. The payoff is that every product NVIDIA ships goes through the systems you'll help build. If that's the kind of problem you want to work on, we'd like to talk.
Senior Photonic Layout Design Engineer
Are you seeking an outstanding opportunity? We are looking for a Senior Photonic Layout Design Engineer – someone who is excited to join a growing group of diverse individuals responsible for handling high-speed mixed-signal & Silicon Photonic Designs! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled 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 pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Join our diverse team today! What You'll Be Doing: - As a Senior Photonics Layout Engineer, you will take ownership of the physical design and verification of cutting-edge photonic integrated circuits (PICs), guiding designs from initial proof-of-concept phases to high-volume manufacturing readiness. You will work within a highly collaborative, multidisciplinary team of photonics, CMOS, packaging, and systems engineers to drive next-generation Silicon Photonics (SiPh) and SERDES products. - Layout Execution & Tape-out Ownership: Lead complex, full-loop manual and automated layout designs for waveguides, modulators, photodetectors, and mixed-signal functions (high-speed/general I/Os, ESD structures). Drive the full tape-out process, including floor planning, waveguide routing, and mask data preparation. - Verification & Mitigation: Execute rigorous post-layout verification (DRC, LVS, fill, density) across multiple stepping versions. Trace defect sources, mitigate layout-dependent issues, and ensure DRC/LVS cleanliness prior to tape-out. - Test Vehicle & Component Development: Own the layout of complex test structures, active/passive full loops, and certification vehicles with large Design of Experiments (DOEs) to optimize for process windows. - Automation & AI-Assisted Workflows: Develop and implement AI-assisted design methods, layout automation scripts, and custom Pcells to improve productivity, reduce development cycle times, and customize DRC/LVS checking flows. What We Need to See: - To succeed in this role, candidates must possess a deep technical understanding of advanced node semiconductor fabrication, sophisticated automation capabilities, and a proven track record of first-time success on high-density chip designs. - BS, MS, or Ph.D. in Electrical Engineering, Physics, or a closely related field (or equivalent experience). At least 6+ years of hands-on, full-chip layout design experience in semiconductor, analog, or silicon photonics industries. - Deep understanding of analog circuit layout, Silicon Photonic constraints, and device physics within advanced sub-micron CMOS and SiPh technologies. - Proven expertise with Cadence Virtuoso (Custom Layout, SDL) and industry-standard verification suites (Calibre, Hercules, ICV, Dracula, or Primeyield). - Strong proficiency in programming and scripting languages (Python, SKILL, Perl, TCL, or C++) for layout automation, file I/O, data processing, and tape-out flows. - Ability to optimize workflows using best-known methods (BKMs), and proactively collaborate with integration, and design rule teams to achieve high-yield manufacturing goals. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 132,000 USD - 207,000 USD for Level 4, and 148,000 USD - 235,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
EDA Methodology Architect
NVIDIA's success builds on a foundation of industry leading hardware. We achieve distinction through extensive design optimization, including combining the best of external EDA with highly optimized, internal EDA tools. Our team develops these tools by fusing advances in parallel computing, machine learning, and specialized algorithms for VLSI design. We are seeking a Senior P&R Methodology Architect to define and own the next generation RTL2GDS flow for advanced nodes (3nm and below) and high performance GPU, CPU and SoC designs. You should have deep, hands‑on experience across the full RTL2GDS flow, with expertise in key stages such as RTL, DFT, synthesis, placement, optimization, CTS, routing, and signoff. Creativity and self-drive to explore is required. Our engineers enjoy unusually high intellectual freedom and the ability to explore broad roles. If you like to work across many technical areas and see your successes directly realized in the world's best AI hardware, it does not get any better than this! What you’ll be doing: - Working directly with core P&R engine developers to define real‑world optimization problems, shape requirements and roadmaps, and provide detailed feedback on engine behavior, QoR, and scalability. - Defining and rolling out next‑gen flows, including refactoring legacy flows and consolidating ad‑hoc solutions into scalable, maintainable frameworks used across multiple design teams. - Designing and running rigorous A/B and multi‑variant experiments to compare flows, engines, and tool settings. Developing Python‑based analytics and ML/GenAI techniques to mine large QoR datasets, recommend flow settings, and automate analysis. - Performing deep root‑cause analysis on QoR issues across engines, tools, and flows, and driving methodologies to resolve the ‘long tail’ of timing closure and performance limiters. - Partnering with architecture, RTL, DFT, synthesis, physical design, power, signoff, and CAD/methodology teams as a key technical leader and bridge. - Driving aggressive PPA and schedule targets and the adoption of new tools and flows across the company. What we need to see: - BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience. - 8+ years physical design experience, with deep expertise in industry standard tools like ICC2/Innovus, PrimeTime/Tempus, etc. - Extensive hands‑on P&R experience taking complex blocks or chips to tape‑out with aggressive PPA targets. - Proven skills in Python, Perl, and TCL flow development. - Strong problem‑solving skills and self‑motivation, demonstrated by simplifying complex, cluttered environments and modernizing legacy tools and processes. - Excellent communication and collaboration skills, with a track record of driving consensus and solving complex issues across distributed design, CAD, and R&D teams. Ways to stand out from the crowd: - Experience collaborating with EDA or internal R&D teams on core engine development, co‑defining features, developing benchmarks and leading validation and deployment. - Expertise in designing and automating A/B tests and large‑scale regressions, and analyzing large QoR datasets to understand trends and drive root‑cause analysis. - Background in advanced‑node and large‑scale designs with exposure to advanced‑node challenges (DFM, variability, EM/IR, power integrity). - Hands‑on experience applying AI/ML or GenAI to physical design, QoR analysis, or flow development will be a strong plus. If working hands‑on from early architecture and RTL through silicon, and serving as the connector between core developers, methodology teams, and users, excites you, we want to hear from you. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Software Architect, AI Systems and Networki...
An applied research team within NVIDIA’s Networking Systems & Software Architecture group is solving some of AI’s hardest infrastructure problems. The team builds systems-level software that moves data between GPUs, nodes, and storage at the speed modern AI demands—spanning low-level transport optimization, hardware-software co-design, and communication frameworks that plug directly into production AI stacks. The team's charter expands into emerging domains including quantum computing interconnects. The Senior Architect role is to own modules and projects end-to-end—from scoping research questions to shipping production code. It calls for a recognized expert who drives technical decisions, pulls in ideas from research and industry, and regularly prototypes new approaches to prove a point. The work lives at the boundary of applied research and production engineering! What you will be doing: Architecting and implementing high-performance communication and memory management libraries for distributed AI Driving hardware-software co-optimization with GPU, DPU, NIC, and switch teams through GPUDirect RDMA, NVLink, and next-generation interconnects Profiling and optimizing data movement across GPU memory, system DRAM, NVMe, and network fabrics Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM Contributing to and maintaining open-source projects, mentoring engineers, conducting design reviews, and prototyping experimental technologies to evaluate their viability What we need to see: 12+ years in systems software and/or networking with demonstrated ownership of complex projects. MS, PhD or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field. Solid understanding of high-performance networking: InfiniBand, RoCE, RDMA, NVLink, GPUDirect. Strong C/C++/Rust systems programming with comfort in performance profiling and low-level debugging. Understanding of ML systems concepts—transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns. Ways to stand out from the crowd: Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. Knowledge of storage networking (NVMe-oF, GPUDirect Storage, S3). Background of Reinforcement Learning systems. With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward‑thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large‑scale, high‑impact data platforms, we’d love to hear from you. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until November 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Implementation Methodology Engineer - GPU
We are looking for an Implementation Methodology Engineer to join NVIDIA VLSI team. If you are looking for a challenging and exciting role and you are a self-starter and highly motivated individual who loves to collaborate and find solutions to hard technical problems, join us today! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled 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 pursue, that only we can tackle, 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. What you’ll be doing: - You will be responsible for all aspects of front-end design implementation methodologies (synthesis, formal-equivalence-checking), flow automation and application support. - Use NVIDIA implementation flows and EDA tool expertise to improve power, performance and area on NVIDIA's most critical designs - You will collaborate with logic designers, physical designers and EDA vendors to solve exciting implementation issues and develop new solutions. - Provide support for EDA tools and flows What we need to see: - BS or MS in Electrical Engineering, Computer Engineering, or related fields (or equivalent experience). - 4+ years of experience in logic design implementation and/or physical design implementation - Deep understanding of logic optimization techniques and relative area, timing, and power trade-offs - Strong understanding of physical design implementation eg: physical synthesis, placement, routing, logic restructuring, etc. - Should be a power user of synthesis and/or place and route EDA tools from Synopsys (DC/FC), Cadence (Genus/Innovus) - Good debugging and problem-solving skills - Strong interpersonal skills along with the ability to work in a dynamic team Ways to stand out from the crowd : - Prior experience in physical implementation - Proficiency in Python, Tcl, Make scripting NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and dedicated people in the world working for us. Are you creative and autonomous? Do you love the challenge of constant innovation and creating the highest performance products in the industry? If so, we want to hear from you. Come, join NVIDIA VLSI team and help build the real-time, cost-effective computing platform driving our success across multiple fields such as Deep Learning and AI, Robotics and Autonomous Driving, Gaming and High Performance Computing. LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
AI and Creator Developer Marketing Manager, China
We are looking for a candidate who is interested in driving the growth of NVIDIA GeForce RTX AI & Creator platform to consumers through engagement with developers. To stand out, demonstrate your sharp understanding on AI ecosystem in China and strong experience on consumer marketing. China is a dynamic and diverse developer communities, with distinct platforms, fast-evolving user behavior, strong local ecosystems, and highly engaged creator networks. This role is critical in helping build meaningful connections with developers and creators across China, while driving the adoption and market relevance of new AI and creator products through localized programs, strong community relationships, and impactful go-to-market execution. An ideal candidate possesses a strong passion for AI evolvement with new graphic technology, a deep understanding of global & China AI trend, a sharp marketing sense and a proven track record of driving successful marketing campaigns. You should be a creative thinker with exceptional communication skills and the ability to collaborate effectively with cross-functional teams. What you’ll be doing: - Identify, develop, and manage co-marketing opportunities with strategic partners, platforms, communities, and creators to expand reach and deepen ecosystem collaboration. - Design and execute localized developer marketing programs that engage technical audiences and creator communities through online and offline channels. - Drive go-to-market planning and execution for new AI and creator products, including launch messaging, content strategy, campaign programs, and community activation. - Partner closely with product, partnerships, developer relations, and regional or global marketing teams to align business goals with local market needs and audience insights. - Create compelling and locally relevant content such as campaign narratives, product launch materials, case studies, community stories, event content, and educational assets for developers and creators. - Gather insights and feedback from developers, creators, and partners in China, then translate those learnings into actionable recommendations for product positioning, messaging, and program improvement. - Support the growth of developer and creator communities by building engagement frameworks, nurturing key relationships, and encouraging ongoing participation in programs, events, and product initiatives. - Track program performance and market response, using data and qualitative feedback to optimize campaign effectiveness, audience engagement, and conversion outcomes over time. What we need to see: - Bachelor’s degree in marketing, business, and/or computer science; AI-related background is a plus. - 5+ years of experience in consumer marketing; AI, creator, PC, or consumer tech industries preferred. - Familiarity with China marketing AI ecosystem, coupled with a solid understanding of graphics technology. - Project management experience with excellent communication, prioritization, listening, collaboration, and organizational skills. - Strong understanding of marketing principles and channels, with pride in delivering excellent work and the ability to multitask. - Daring, driven, proactive, and adaptable, with a can-do attitude and strong attention to detail. - Ability to work well within a team, with self-discipline, flexibility, and accountability to complete tasks effectively. - Passion for learning, innovation, and continuously building marketing knowledge. Ways to stand out from the crowd: - Experience at developer marketing, especially AI or PC industry oriented. - Understands how to engage with young consumers on social media. - Sharp sense on marketing with creativity. - Understanding of AI, creator will be a good plus 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. If you're creative and autonomous, we want to hear from you. LI-Hybrid
Senior System Software Engineer - AI Performance a...
A key part of NVIDIA's strength is our sophisticated analysis / debugging tools that empower NVIDIA engineers to improve perf and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for AI researchers and SW/HW teams running AI workload in GPU cluster. As a member of the software development team, we will work with users from different departments like Architecture teams, Software teams. Our work brings the users intuitive, rich and accurate insight in the workload and the system, and empower them to find opportunities in software and hardware, build high level models to propose and deliver the best hardware and software to our customers, or debugging tricky failures and issues to help improve the performance and efficiency of the system. What you’ll be doing: - Build internal profiling and analysis tools for AI workloads at large scale - Build debugging tools for common encountered problems like memory or networking - Create benchmarking and simulation technologies for AI system or GPU cluster - Partner with HW architects to propose new features or improve existing features with real world use cases What we need to see: - BS+ in Computer Science or related (or equivalent experience) and 5+ years of software development - Strong software skills in design, coding (C++ and Python), analytical, and debugging - Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference. - Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking - Experience with NVIDIA GPUs, CUDA Programming and NCCL - Motivated self-starter with strong problem-solving skills and customer-facing communication skills - Passion for continuous learning. Ability to work concurrently with multiple global groups Ways to stand out from the crowd: - Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms - Solid experience in large AI job performance analysis for training/inference workload - Knowledge of Linux device drivers and/or compiler implementation - Knowledge of GPU and/or CPU architecture and general computer architecture principles
Solutions Architect - AI Technology Center, Founda...
NVIDIA AI Technology Center is seeking outstanding Senior Solutions Architects to catalyze the global research community by embedding NVIDIA as a core scientific collaborator. We move beyond standard technical support to act as elite research partners, driving the adoption of NVIDIA's platform through high-impact, co-authored breakthroughs and the shared pursuit of frontier AI discoveries. Primary focus on building foundation model engagements with researchers and developers at our key partner researcher from universities and joint labs. You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts dedicated to frontier model development. This role is an excellent opportunity to work in an interdisciplinary team with the latest technologies at NVIDIA! What you will be doing: - Create fruitful technical engagements with top developers and influential researchers from the universities or enterprises building foundation models in Korea and lead strategic relationships with them. - Help them develop AI models more efficiently by proposing state-of-the-art training and optimization frameworks including Megatron-LM, Megatron-Bridge, NeMo-RL, or TensorRT-LLM. - Promote the results of the collaboration between NVIDIA and those teams with the support of marketing teams by publishing press releases and celebrate together by presenting them at GTC. - Advise on the transition from experimental code to large-scale, production-ready research environments, demonstrating the performance leap provided by the NVIDIA technology stack. What we need to see: - PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - Proven experience in managing complex technical projects and navigating corporate strategic goals - 5+ year hands-on experience in full AI model lifecycle, including pre-training, supervised fine-tuning, post-training such as reinforcement learning, optimization, and evaluation. - Experience with NVIDIA GPUs and software libraries - Strong problem-solving and debugging skills - Excellent presentation, communication, and collaboration skills - Strong written and oral communication skills in English. Ways to stand out from the crowd: - Good track record of academic research publications - Experience working across academia, industry and the government - Understanding of infrastructure factors that can affect AI model development such as GPU architecture, server block diagram, or networking bandwidth among GPU servers or between GPU servers and shared storage. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you are creative and autonomous, we want to hear from you! NVIDIA is committed to encouraging a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Solutions Architect - AI Technology Center, Scient...
NVIDIA AI Technology Center is seeking outstanding Senior Solutions Architects to catalyze the global research community by embedding NVIDIA as a core scientific collaborator. We move beyond standard technical support to act as elite research partners, driving the adoption of NVIDIA's platform through high-impact, co-authored breakthroughs and the shared pursuit of frontier AI discoveries. Primary focus on scientific application engagements with researchers and developers at our key partner researcher from universities and joint labs. You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts dedicated to HPC applications. This role is an excellent opportunity to work in an interdisciplinary team with the latest technologies at NVIDIA! What you will be doing: - Analyze key scientific applications of top researchers from the universities or enterprises in Korea, understanding data type, input and output, workflow, runtime between CPU and GPU, proportion of MPI communications, etc. - Help them accelerate their applications by resolving the bottleneck that can be improved in latency or runtime perspectives using NVIDIA CUDA libraries and SDKs. - Promote the results of the collaboration between NVIDIA and those teams with the support of marketing teams by publishing press releases and celebrate together by presenting them at GTC. - Advise on the transition from experimental code to large-scale, production-ready research environments, demonstrating the performance leap provided by the NVIDIA technology stack. What we need to see: - PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - Proven experience in managing complex technical projects and navigating corporate strategic goals - 5+ year hands-on experience in one or two of HPC fields, for example, electronic structure calculations, molecular dynamics, computational fluid dynamics, astrophysics, numerical weather prediction, or quantum computing - Experience with NVIDIA GPUs and software libraries - Strong problem-solving and debugging skills - Excellent presentation, communication, and collaboration skills - Strong written and oral communication skills in English. Ways to stand out from the crowd: - Good track record of academic research publications - Experience working across academia, industry and the government - Experience with AI physics models and model architecture including developing, defining, training, and deploying open or proprietary models. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you are creative and autonomous, we want to hear from you! NVIDIA is committed to encouraging a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Solutions Architect Networking
NVIDIA is looking for Senior Networking Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer! What You'll Be Doing - Primary responsibilities will include building AI/HPC infrastructure for new and existing customers. - Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting. - Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement. - Maintain services once they are live by measuring and monitoring availability, latency, and overall system health. - Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements. What We Need To See - BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields. - At least 5+ years of professional experience in networking fundamentals, TCP/IP stack, and data center architecture - Proficiency in configuring, testing, validating, and resolving issues in LAN networks, especially in medium to large-scale HPC/AI environments. - Advanced knowledge of EVPN, BGP, OSPF, VXLAN protocols. - Hands-on experience with network switch/router platforms like Cumulus Linux, SONiC, IOS, JunosOS, and EOS. - Extensive experience delivering automated network provisioning solutions using tools like Ansible, Salt, and Python. - Ability to develop CI/CD pipelines for network operations. - Strong focus on customer needs and satisfaction. - Self-motivated with leadership skills to work collaboratively with customers and internal teams. - Strong written, verbal, and listening skills in English are essential. Ways To Stand Out From The Crowd - Familiarity with cloud networks (AWS, GCP, Azure) is a plus. - Linux or Networking Certifications. - Experience with High-performance computing architectures. Understanding of how job schedulers (Slurm, PBS) work. - Cluster management technologies knowledge (bonus credit for BCM (Base Command Manager).) - Experience with GPU (Graphics Processing Unit) focused hardware/software.
Senior Data Center Infrastructure Specialist
NVIDIA is looking for a Data Center Deployment Specialist to join its Professional Services team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest data centers in the world! NVIDIA is looking for someone with the ability to work on a dynamic customer-focused team that requires excellent interpersonal skills. As a Data Center Infrastructure Specialist, you will be interacting with customers, partners, and internal teams, to analyze, define and implement large scale Datacenter projects. The scope of these efforts includes a combination of Datacenter Infrastructure design and cluster deployment planning. What you will be doing: - Design and implement flawless data center infrastructure solutions to meet the needs of our customers. - Collaborate with cross-functional teams to ensure the successful deployment of data center infrastructure. - Datacenter Planning: Floor Plan, Rack Elevation, Simulation - Cable deployment planning including - ensuring requirements are accurate such as number and type of connections, port assignments, and timing of activity while following standard methodologies, Point-to-Point Design. - Deploy and Support NVIDIA products. - Validating and updating all related work instructions for Datacenter activities. - Responsible for providing input for Data Center Standards updates as required; balancing multiple activities and priorities; participate in projects calls. - Documenting processes and keeping event logs What we need to see: - 3+ years of proven experience as a data center infrastructure engineer, field service engineer or similar with background in designing and implementing data center infrastructures. - Bachelor's degree or equivalent experience in a relevant field. - In-depth knowledge of data center environments, servers, and network equipment. - Extensive experience in installing, monitoring, and maintaining data center equipment. - Solid understanding of networking, storage, and virtualization technologies. - Excellent problem-solving skills and attention to detail. - Ability to work as part of a team, in a fast and highly dynamic environment. - Exceptional communication and interpersonal skills. - Proficiency in documenting processes. - Willingness to travel, around 30% Way to stand out from the crowd: - Network certification such as: Cisco Certified Network Associate (CCNA), Juniper Networks Certified Associate - Junos (JNCIA-Junos) - Knowledge with InfiniBand Technology - Collaboration with R&D and network engineering teams. - Excellent interpersonal communication and on-site coordination skills. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world, working for us. Our commitment to pushing boundaries and delivering exceptional solutions is unparalleled. As a Data Center Infrastructure Specialist, you will play a key role in shaping the future of computing and driving the success of our clients. At NVIDIA, we are an equal opportunity employer. We value diversity and are committed to creating an inclusive and supportive work environment for all employees. If you are a proactive and driven individual, creative with a strong interest in current technology trends, this is the opportunity you have been waiting for. Join us at NVIDIA and be part of our journey to shape the future of computing. Apply now and let's work together to make a difference!
Senior AI Security Architect
NVIDIA Networking Product Security team is seeking an outstanding technical AI Security Architect with hands-on experience in secure software development lifecycle (SDLC) practices, AI-assisted engineering workflows, and agentic development environments. In this role, you will help define and transform how NVIDIA Networking teams build secure AI products by designing and deploying next-generation development methodologies powered by AI agents and intelligent automation. You will drive the integration of secure agentic development environments into the SDLC, enabling developers and security teams to build, validate, and secure AI products more efficiently and at scale. The ideal candidate combines deep security expertise with practical software development experience and a strong understanding of how AI-assisted development environments can reshape modern engineering practices. What you’ll be doing: - Define and evolve secure SDLC methodologies for NVIDIA Networking AI products using AI-assisted and agentic development environments. - Design frameworks and best practices for the secure adoption of AI coding assistants, autonomous agents, and AI-driven engineering workflows. - Architect secure agentic development environments that improve developer productivity while maintaining strong security controls and governance. - Partner with architecture, infrastructure, security, and R&D teams to integrate AI-native workflows into the software development lifecycle. - Define security guardrails, validation mechanisms, and policy enforcement for AI-assisted software development processes. - Design and recommend security architectures and controls to satisfy internal and external security requirements. - Lead initiatives that modernize secure engineering practices across large-scale development organizations. - Mentor developers, architects, and security engineers on secure AI development methodologies and best practices. What we need to see: - Academic degree in Computer Science, Electrical Engineering, Cybersecurity, or related field. Equivalent experience will also be considered. - 5+ years of experience in security engineering, application security, or security architecture. - Strong understanding of modern SDLC processes, developer workflows, and secure software engineering practices. - Hands-on experience designing, building, or operating agentic development environments or AI-assisted engineering platforms. - Experience securing AI applications and integrating AI tools into enterprise development workflows. - Familiarity with AI coding assistants, autonomous agents, LLM frameworks, and orchestration systems. - Experience defining security policies and governance for AI-enabled development environments. - Ability to drive significant organizational and engineering process changes across large-scale teams. - Ability to work independently and collaboratively in a constantly evolving environment. - Excellent communication and interpersonal skills. Ways to stand out from the crowd: - Experience building AI-native developer platforms or internal engineering productivity systems. - Experience managing or influencing large R&D organizations and engineering transformation initiatives. - Familiarity with cloud-native security, Kubernetes, and large-scale distributed systems. - Experience designing governance frameworks for enterprise AI adoption. - Demonstrated thought leadership through publications, conference talks, or open-source contributions related to AI security or developer tooling. With highly competitive salaries and a comprehensive benefits package, 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 on the planet working for us and, due to unprecedented growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior LLM Agents Architect
We don't just build the hardware and software that powers the AI revolution — we are building the AI that designs the next generation of both. Our team sits at the intersection of inference software and GPU architecture, creating autonomous LLM-driven systems that reason about hardware, write high-performance CUDA, and automate the complex loops of architectural simulation, analysis, and optimization. We are looking for a senior LLM Agents Architect to work hands-on with hardware architects, verification engineers, GPU performance experts, and software developers to build end-to-end agent flows that drive significant improvements in kernel optimization, architectural exploration, and developer efficiency. What you'll be doing: - Design and build agentic AI systems that generate, analyze, and optimize GPU compute kernels — targeting speed-of-light performance on NVIDIA hardware. - Collaborate with GPU architects and performance engineers to encode domain expertise — memory hierarchy trade-offs, occupancy tuning, instruction-level reasoning — into agent workflows that rival hand-tuned optimization. - Build automated performance forensics agents capable of ingesting large-scale simulation traces and Nsight profiler data to identify bottlenecks and propose architectural or software mitigations. - Partner with HW architects to develop agentic flows for GPU architectural studies — enabling rapid what-if analysis across micro-architecture configurations such as cache sizing, memory controller design, and compute unit scaling. - Explore agentic approaches to HW/SW co-design challenges, including replacing or augmenting graph-compiler functionality (e.g., TorchInductor) with LLM-driven optimization and code-generation pipelines. - Rapidly prototype and thoughtfully productize; integrate with internal services, utilize GPU capabilities, remove bottlenecks, and deliver fitting solutions. - Set up evaluation backbone using offline golden sets and online telemetry for confident iterations, cost control, and safe improvements. - Mentor and improve teams through insights in agent orchestration, prompting, RAG, observability, crafting documentation and playbooks for NVIDIA's teams. What we need to see: - 8+ years in applied ML/AI or large-scale systems, with 2+ years crafting agentic or LLM-powered applications in production environments. - B.Sc in Computer Science / Electrical Engineering. - Solid grounding in computer architecture: memory hierarchies, parallelism models, pipelining, and cache behavior. Specific familiarity with NVIDIA GPU architecture — streaming multiprocessors, warp scheduling, shared/global memory model, and occupancy reasoning — is essential. - Hands-on CUDA programming experience: writing, profiling, and optimizing GPU kernels — not just calling into CUDA-accelerated libraries. Comfortable with tools such as Nsight Compute, Nsight Systems, or equivalent profiling workflows. - Proven ownership of at least one end-to-end agentic system or LLM application: requirements, architecture, implementation, evaluation, and incremental hardening in production — not just experience with off-the-shelf frameworks. - Strong software engineering skills in Python and one systems language (C++ preferred). - Proficient in tool use, RAG pipelines, and model adaptation techniques for building agentic systems. - Demonstrated ability to collaborate with HW/SW domain experts and translate their heuristics into deterministic tools, constraints, and evaluation metrics. - Excellence in communication and facilitation: aligning diverse collaborators, documenting decisions/assumptions, and influencing without authority. - Track record of building observability for AI systems: dataset/version management, offline test suites, online telemetry, guardrails/safety checks, and rollback plans. Ways to stand out from the crowd: - Familiarity with the PyTorch compilation and lowering stack (torch.compile, TorchDynamo, TorchInductor, Triton, down to PTX), and with GPU graph compilers, kernel fusion strategies, or auto-tuning frameworks. - Background in performance engineering for HPC or GPU-accelerated workloads, including experience with performance modeling or hardware simulators. - Familiarity with distributed processing, multi-GPU workloads, and networking (e.g., NVLink, InfiniBand). - Familiarity with frontier agentic coding tools (e.g., Claude Code, Codex, Cursor) — understanding their underlying architecture: tool orchestration, context management, and autonomous task execution patterns. - Hands-on experience building a domain-specific coding agent — whether on top of frontier agentic harnesses (e.g., Claude Code, Codex SDK) or lower-level agent frameworks (e.g., LangChain/LangGraph deep agents, CrewAI). Comfortable with the design choices that make a coding agent useful in practice: task scoping, tool and context curation, evaluation, and failure recovery Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
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