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Senior Software Engineer, AI Inference Systems
We are seeking highly skilled and motivated software engineers to join us and build AI inference systems that serve large-scale models with extreme efficiency. You’ll architect and implement high-performance inference stacks, optimize GPU kernels and compilers, drive industry benchmarks, and scale workloads across multi-GPU, multi-node, and multi-cloud environments. You’ll collaborate across inference, compiler, scheduling, and performance teams to push the frontier of accelerated computing for AI. What you’ll be doing: - Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding, data/tensor/expert/pipeline-parallelism, prefill-decode disaggregation. - Develop, optimize, and benchmark GPU kernels (hand-tuned and compiler-generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high-level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization. - Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry-leading MLPerf Inference benchmarking suite. - Architect the scheduling and orchestration of containerized large-scale inference deployments on GPU clusters across clouds. - Conduct and publish original research that pushes the pareto frontier for the field of ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into NVIDIA’s software products. What we need to see: - Bachelor’s degree (or equivalent expeience) in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE) with 7+ years of experience; alternatively, Master’s degree in CS/CE/SE with 5+ years of experience; or PhD degree with the thesis and top-tier publications in ML Systems, GPU architecture, or high-performance computing. - Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories. - Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang). - Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute). - Experience with containers and orchestration (Docker, Kubernetes, Slurm); familiarity with Linux namespaces and cgroups. - Excellent debugging, problem-solving, and communication skills; ability to excel in a fast-paced, multi-functional setting. Ways to stand out from the crowd - Experience building and optimizing LLM inference engines (e.g., vLLM, SGLang). - Hands-on work with ML compilers and DSLs (e.g., Triton, TorchDynamo/Inductor, MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores). - Experience contributing to containerization/virtualization technologies such as containerd/CRI-O/CRIU. - Experience with cloud platforms (AWS/GCP/Azure), infrastructure as code, CI/CD, and production observability. - Contributions to open-source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts. At NVIDIA, we believe artificial intelligence (AI) will fundamentally transform how people live and work. Our mission is to advance AI research and development to create groundbreaking technologies that enable anyone to harness the power of AI and benefit from its potential. Our team consists of experts in AI, systems and performance optimization. Our leadership includes world-renowned experts in AI systems who have received multiple academic and industry research awards. If you’re excited to build systems, kernels, and tools that make large-scale AI faster, more efficient, and easier to deploy, we’d love 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 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 2, 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 High-Performance LLM Training Engineer
NVIDIA is seeking a Principal Engineer to drive the performance of large-scale AI training and post-training workloads across NVIDIA’s full hardware and software stack. This role sits at the intersection of distributed training, GPU architecture, systems software, deep learning frameworks, and performance engineering. You will analyze and optimize frontier-scale LLM workloads running on thousands of GPUs, drive improvements across frameworks such as PyTorch, JAX, NeMo, and NeMo RL, and use insights from real workloads to help shape future NVIDIA GPU, system, and software roadmaps. We are looking for a deeply technical leader who can operate across abstraction layers: from application-level training behavior to framework/runtime internals, CUDA libraries, communication collectives, memory systems, networking, and GPU architecture. At this level, success means both directly improving performance directly as well as setting technical direction, raising the bar for the organization, and influencing multi-functional decisions across NVIDIA. What you will be doing: - Lead end-to-end performance analysis and optimization of innovative LLM pre-training and post-training workloads on the latest NVIDIA hardware and software platforms. - Drive workloads closer to speed-of-light performance by identifying and removing bottlenecks across compute, memory, communication, scheduling, parallelism strategy, kernel efficiency, framework overhead, and system-level scaling. - Develop production-quality software, tools, models, benchmarks, and analysis infrastructure that improve training performance, efficiency, and developer velocity across NVIDIA’s AI software stack. - Build and refine performance models, workload characterizations, and simulation methodologies to guide future GPU, networking, system, and software architecture decisions. - Serve as a technical authority for AI training performance, partnering closely with teams across GPU architecture, systems, CUDA libraries, compilers, networking, frameworks, product management, and applied AI. - Translate workload insights into concrete hardware and software recommendations, and advocate for changes that improve performance and efficiency across the AI ecosystem. - Mentor and provide technical leadership to engineers across the organization, helping establish best practices for large-scale AI performance analysis and optimization. What we need to see: - A MS, or PhD (or equivalent experience) in Computer Science, Electrical Engineering, Computer Engineering, or a related field, with 12+ years of relevant work or research experience. - Demonstrated principal-level technical impact in one or more of the following areas: large-scale AI training systems, GPU performance optimization, distributed systems, high-performance computing, ML frameworks, compilers/runtimes, or hardware/software co-design. - Deep hands-on experience analyzing and optimizing performance of large-scale deep learning workloads, especially transformer-based models, LLM pre-training, reinforcement learning, fine-tuning, or other post-training workloads. - Strong understanding of GPU and AI accelerator architecture from individual accelerators to datacenter-scale systems. - Experience with distributed training techniques such as data parallelism, tensor parallelism, pipeline parallelism, expert parallelism, sequence parallelism, activation checkpointing, mixed precision training, and communication/computation overlap. - A strong track record of using profiling, tracing, benchmarking, and performance modeling tools to diagnose complex bottlenecks and drive measurable improvements. - Excellent communication and technical leadership skills, with the ability to influence architecture and software decisions across multiple teams without relying on direct authority. GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with the major systems companies and every major cloud service provider to make GPUs available in data centers and in the cloud. We craft computers and software to bring AI to edge devices, such as self-driving cars and autonomous robots. AI has the potential to spur a wave of social progress unmatched since the industrial revolution. This opportunity offers you the ability to collaborate with some of the most forward-thinking and hard-working people in the world, shaping the future of AI in a creative and autonomous work environment that encourages innovation. If you're passionate about working across the full hardware & software stack—from GPU architecture to application code—to achieve optimal performance, 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 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 2, 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 BMC Firmware Development Engineer
NVIDIA’s 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 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're looking to grow our company and establish teams with the most thoughtful people in the world. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement. What you’ll be doing: - Designing, implementing, and delivering innovations for managing GPU based AI servers with focus on OOB management, firmware development, server architecture and building systems for enterprise. - Working with a global team of BMC developers on NVIDIA server designs. - Designing and developing performance optimized active monitoring BMC solutions using DMTF Standards including MCTP, Redfish, SPDM and PLDM specifications. - Instrumenting code to ensure maximum code coverage, writing and automating unit tests for each implemented module and maintain detailed unit test case reports. - Providing software quality reports based on static analysis, code coverage, CPU load. - Partner with security team to ensure developed code is in line with product security goals. - Working closely with hardware teams to influence hardware design and review HW architecture & schematics. - Working with QA/Test architects to come up with proper test tools and automation for qualifying the whole system software and firmware stack. What we need to see: - Bachelor’s Degree or higher in Electrical Engineering or Computer Science, and 5+ years of experience, with demonstrated strong ability as individual contributor. - Domain expertise in BMC Firmware development on X86 or ARM Platforms including BMC-BIOS communication, thermal management, power management, firmware update, device monitoring, firmware security, etc. - Strong experience with AMI/Insyde or OpenBMC Firmware architecture. - Be able to lead BMC firmware development through the whole project developing phases and success to mass production. - Solid experience of end-to-end delivery of high-end enterprise servers from definition to customer deployment. - Solid understanding of low-level interfaces between SBIOS, BMC and OS like I2C/SPI/PCIe/JTAG etc. PCIe enumeration, IO at platform level for enterprise systems. - Experience working closely with HW teams, ODMs and vendors to introduce and support server platforms. - Experience with C/C++ development, bash/python for scripting, and debugging skills in embedded Linux operating environments. - You should possess excellent written and oral communication skills, good work ethics, high sense of team-work, love to produce quality work and commitment to finish your tasks every single day. You are a self-starter who loves to find creative solutions to exciting problems. Ways to stand out from the crowd: - Contributor to industry standards like Open Compute, IPMI, DMTF Standards, and open source. - Proven record in delivering BMC or equivalent manageability stack for enterprise servers with AMI SPX firmware stack. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. 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, gender, sexual orientation, age, marital status, veteran status, or disability status.
Senior Solutions Architect - AI Factory Deployment
We are seeking an ambitious Senior Solutions Architect - AI Factory Deployment to join our NVIDIA Infrastructure Specialists team in Santa Clara! This role is uniquely positioned to develop, deploy, and validate AI factories end to end. You will focus on running and debugging AI/LLM workloads and benchmarks on Linux-based GPU clusters, using NCCL and collectives like AllReduce and AllToAll to improve performance and scalability. As part of our world-class team, you will bring to bear observability and automation to improve benchmarks and validation. You will serve as the expert when workloads or benchmarks do not perform flawlessly. You will collaborate across NVIDIA to ensure AI factories are prepared for customers, validating hardware and software for modern AI deployments. What You Will be Doing: - Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters. - Ensure configurations align with guidelines for NCCL, collectives, and distributed training frameworks. - Own the execution of key AI/LLM benchmarks, including setup, orchestration, result collection, and analysis. - Investigate and resolve issues when training jobs or benchmarks fail, hang, or underperform. - Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health. - Develop automation (Python, Shell) for running benchmarks, collecting results, and performing regression checks - Examine communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll. - Recommend changes to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency. - Work closely with hardware, software, networking, datacenter, and product teams to prepare AI factories for customer use. - Contribute to documentation, guidelines, and readiness collateral that support internal collaborators and customer-facing teams. What We Need to See: - Bachelor’s degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or related field. - More than 6+ years of experience managing Linux-based systems in HPC, distributed systems, or extensive AI/ML settings. - Hands-on experience running AI/ML workloads on multi-GPU and/or multi-node clusters, with practical knowledge of NCCL. - Solid grasp of collective communication patterns, particularly AllReduce and AllToAll, and how they are applied in contemporary ML/LLM training. - Familiarity with LLM training and/or inference workflows using frameworks such as PyTorch or TensorFlow. - Proficiency with Python and Shell/Bash for scripting, automation, and tooling. - Experience with benchmarking (crafting, executing, and interpreting performance benchmarks). - Comfortable working with observability data (metrics, logs, dashboards) to troubleshoot and optimize complex distributed workloads. - Strong communication skills and the ability to work effectively with cross-functional teams. Ways to Stand Out From the Crowd: - Experience with AI factory or large-scale AI infrastructure build, deployment, or operations. - Background in HPC performance engineering, SRE, or systems performance analysis for GPU-accelerated environments. - Familiarity with observability stacks (e.g., metrics/monitoring, logging, tracing systems) used for large distributed systems. - Experience building automation and CI-style pipelines for running and validating benchmarks at scale. - Demonstrated desire to use AI to solve practical problems, improve workflows, and guide data-driven decisions. 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 3, 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 Signal and Power Integrity Engineer
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! This position offers the opportunity to have real impact in a multifaceted, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. What you'll be doing: - Lead board/system SI design activities, PCB stack up design, material selection, design guide implementation, layout review, and post-layout analysis. - System-level signal integrity simulation of PCIE, LPDDR/DDR/GDDR, MIPI, HDMI, USB and other interfaces. - Analyze and optimize Power delivery network (PDN) on PCBs. - Work closely with Package and PCB Design teams crafting solutions for system SI/PI performance. - Work with Application Engineering supporting customer board designs. - TDR & VNA measurement for PKG/PCB material characterization and model correlation What we need to see: - BS/MS in Electrical Engineering (or equivalent experience) with minimum 4 years of experience as a SI/PI engineer - Good understanding of electromagnetics, channel components and transmission line theory - Experience with design and implementation of one or more high speed electrical interfaces, such as PCIE, LPDDR/DDR/GDDR, MIPI, HDMI, USB etc. - Hands on experience with HFSS, Sigrity, Hspice or similar industry standard simulation tools - Experienced with Cadence Allegro PCB designer and Constraints Manager and or other PCB stack up designer tools. - Understanding of impacts of high-volume PCB manufacturing on channel signal integrity Ways to stand out from the crowd: - Expertise in one or more of the high-speed interface SI/PI designs on any industry standard system platforms. - Exposure to package design, interface timing budgets and system modeling - Familiarity with high-speed transmitter, receiver design and various equalization schemes - Familiarity with various signaling schemes like NRZ, PAM4 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 3, 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.
Product Manager, AI Platform SW - Agentic AI Kerne...
NVIDIA's AI Software Platforms team is building the next generation of agentic AI infrastructure that lets coding agents synthesize, optimize, and deploy GPU kernels automatically. This job focuses on crafting AI kernels that connect data pipelines, evaluation suites, and GPU-accelerated runtimes. This helps developers safely release faster, better-performing inference and training solutions. As Product Managers at NVIDIA, we enable developers to be successful on the NVIDIA platform and push the boundaries of what is possible with AI deployments. In this role, you will act as the internal champion for AI agents and LLM-based coding workflows that generate optimized kernels. You'll partner closely with engineering, research, and customers to define strategy, develop roadmaps, and build products that span the entire agent lifecycle — from data collection and synthetic data generation to evaluation, deployment, and continuous improvement. What you'll be doing: - We architect agent-focused products that let coding agents generate, refactor, and optimize CUDA kernels and graph-level execution plans across diverse GPU architectures. - Define the end-to-end data lifecycle for agent training and evaluation, including dataset curation, artificial data creation, and benchmark suites for correctness, latency, and adaptability. - Partner with CUDA, kernel, and compiler engineering teams to integrate agents with compilers, profilers, execution sandboxes, and runtimes in a safe, observable way. - We collaborate with internal and external developers, NVIDIA leaders, and ecosystem partners to drive multi-agent orchestration, prioritize features, and deliver launches and messaging for agentic AI kernel generation. What we need to see: - 7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; we care deeply about end-to-end ownership and impact. - Proven experience in the AI agent or LLM space, including developing or productizing coding agents. Experience with multi-agent orchestration and self-healing or code loops that improve over time is required. Candidates should also have worked on connecting agents to compilers or execution environments. - Proven record of crafting and releasing automated testing or evaluation suites. These suites measure agents on non-subjective metrics such as correctness, performance, and latency. We rely on data to guide both development and iteration. - BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems. Ways to stand out from the crowd: - PhD or equivalent experience in Computer Engineering, Computer Science, or another technical specialty. - Track record building or launching coding-agent platforms or copilots used by development teams at scale, and contributions to performance-critical open-source projects (e.g., Triton, TVM, FlashAttention, kernel libraries, agent frameworks) with clear community adoption and impact. - Research experience in GPU kernel optimization, collective or group communication algorithms, multi-agent systems, or ML model serving / inference architectures that shows how you think about systems end-to-end. - Experience crafting cost-per-inference or cost-per-token models that incorporate hardware utilization, energy efficiency, and cluster scaling, and using those models to guide product strategy and tradeoffs. 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 - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 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.
Strategic Account Manager - CSP
NVIDIA is an accelerated computing platform company, that includes GPU, DPU, Networking and software for Professional Visualization, Accelerated Computing, Generative AI, ML. Be an integral part of a team responsible for a significant and rapidly growing revenue contribution at NVIDIA. We are looking for a strategic account manager to raise awareness, increase the adoption and accelerate the development and deployment of all NVIDIA's accelerated computing platform with a major CSP. This full-time position requires strong technical background and close working relationships with CSP organizations, NVIDIA Solution Architects, Business Units, and Developer Relations, to drive revenue and partnerships for the company through adoption of NVIDIA's accelerated platforms. What you’ll be doing: - Lead customer engagement and business development activity with a major CSP organizations. - Develop excellent strategic relationships with R&D teams to understand customers' software and accelerated computing needs with a focus on Visualization and Generative AI, DL/ML workloads. - Partner and collaborate with technical teams on GPU application acceleration. - Be the link between the product team and the customer (roadmap updates, tech communications…) What we need to see: - BSEE or equivalent experience (MSEE Preferred) and 12+ years of technical sales, business development or product Management - A proven understanding of the business issues of large CSP, accelerated Computing/ Data Center technology/ Deep learning & machine learning. - Experience selling accelerated solutions to senior executives at named accounts. A real passion for getting things done in a complex sales and technology environment. - Demonstrated track record leading significant revenue and overachieving targets to meet stretch goals. - Ability to provide thought leadership, think strategically and effectively communicate vision (both written and verbal) and influence cross-functionally. Excellent communication skills. Ways to stand out from the crowd: - Strong Background in modern Data Center technology, Professiona Visualization technology and Deep learning/Machine learning. Experience engaging with large hyperscalers. - Successful management of technical products throughout their lifecycle. Track record of successfully growing revenue for new innovative technology-based solutions. Proven ability to build and lead in a matrix-managed team culture. - Excellent communication skills and ability to persuade -- using simple communications that convey sophisticated concepts in a compelling, concise, and creative way. Strong executive presence, polish, and political savvy. 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 cash compensation will be determined based on your location, experience and the pay of employees in similar positions with 85% paid through base salary and 15% variable compensation. The cash compensation range is 224,000 USD - 356,500 USD for Level 5, and 248,000 USD - 396,750 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 3, 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 GPU Compiler Development Engineer
We are looking for experienced Systems SW Compiler Engineers for an exciting role in our PTX (Parallel Thread Execution) Compiler Development team. Join the PTX Compiler team and help drive PTX language design and PTX compiler evolution. PTX enables all GPU Computing applications including HPC, Deep Learning and Autonomous Driving. PTX provides a stable programming model and portable instruction set Architecture (ISA) for NVIDIA GPUs and used by all Compute programming languages compiled to NVIDIA GPUs. PTX is also used as a compiler target by various non-NVIDIA compilers. Work with NVIDIA GPU Architecture and CUDA Programming model teams to build abstractions to expose new GPU features in portable and performant ways in PTX ISA. PTX Compiler (PTXAS) apart from implementing PTX ISA is responsible for PTX Compiler Front End, interaction with optimizer and runtime aspects involving object files, debug information, linkers, loaders and Driver Compiler Interface. As a senior member of the team, you will be responsible for leading efforts to enhance PTX Compiler infrastructure to enhance it to support new compilation models for DL and Generative AI codes. You will be contributing towards evolving programming model for Generative AI and DL applications on GPUs. What you will be doing: - Provide stewardship for PTX ISA and PTX Compiler infrastructure for Generative AI and DL. - Collaborating with architecture and programming model teams to design and implement programming models for next generation GPUs. - Working closely with others to help design compilation stack and strategies for AI and DL workloads. - Collaborate closely with teams developing other related components to ensure compatibility, robustness and high-quality code generation. What we need to see: - BS (or equivalent experience), MS or Ph.D. in Computer Science, Computer Engineering, or related fields. - 6+ years of experience in the area of compiler front end, programming language designs, Compilers/Linkers. - Superb analytical and C/C++ programming skills. - Able to expertly use AI tools and maintain AI generated artifacts - Experience in any one area of compiler development including feature support, code generation and compiler infrastructure. - Excellent and strong interactive, verbal and written communications skills. - Understanding of any Processor ISA (GPU ISA a plus). - Good track record of developing, driving and delivering software products. Ways to stand out from the crowd: - Experience in Programming Languages design and drafting programming language standards. - Knowledge of GPU development and compute APIs such as CUDA, and OpenCL. - Development experience in LLVM IR, MLIR With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Deep Learning, Artificial Intelligence, Autonomous Vehicles, Virtual Reality, etc. Our diverse team of talented, capable, and professional people are our greatest asset! 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 3, 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.
Solutions Architect, GenAI
We are looking for a Solutions Architect with experience in GenAI (LLM) model building. This is a highly technical role that requires deep expertise in generative AI, large language models (LLMs), and scalable software engineering practices. We need a passionate, hard-working, expert and creative individual to help us pursue the many opportunities in this region. A Solution Architect is the first line of technical expertise between NVIDIA and our customers, as well as our partners. Your duties will vary from solutions design, training/workshops, troubleshooting, project coordination, industry and marketing speaking engagements, customer relationship management and more. You will primarily support Singapore, but will need to support the wider South East Asia region if required. What you'll be doing: - Be an expert and help customers to customize GenAI (LLM) models and optimise the training performance at scale. - Lead workshops and trainings on NVIDIA's technologies. - Closely partner with other Solutions Architects, engineering, product and business teams at NVIDIA to build GenAI full stack solutions for industry vertical and enterprise use cases. - Work with business managers to thoughtfully craft the vision, actionable and effective strategies for the group. - Encourage industry leaders by articulating the business value from the state of the art in Generative AI. 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+ overall years of work-related experience in deep learning, data science or software development with knowledge of parallel computing with GPUs. Specifically focusing on generative AI at scale, with emphasis on training Large Language Models (LLMs) at scale. - Clear written and oral communication skills with the ability to collaborate with management and engineering. Share knowledge with clients, partners and co-workers. - Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences. - Professional or native language proficiency in English and Mandarin. - Ability to travel up to 30% of the time to support customer in South East Asia and beyond. Ways to stand out from the crowd: - Hands-on experience with NVIDIA's NeMo SDKs or Megatron. - Demonstrable ability to customize LLM models with new capabilities as well as for training speed, memory efficiency, and resource utilization. - Familiarity with containerization technologies (e.g., Docker or enroot/pyxis, etc.) and orchestration tools (e.g., Slurm or Kubernetes, etc.) for scalable and efficient model building. 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.
GPU Profiling Software Engineer
At NVIDIA, we build groundbreaking products for the following sectors: Deep Learning, High Performance Computing, Gaming, VR, and Automotive. See your efforts in action as developers use your tools to debug, profile and analyze the performance of their systems/applications using the low-level library that you helped to craft as a member of the GPU Foundations Developer Tools team! Innovate as you develop the performance analysis capabilities of NVIDIA hardware along with the Nsight tools and the foundation library to support next generation accelerated computing at datacenter scale. As a system software engineer in the Developer Tools group, you will be developing software that empowers GPU application developers to build outstanding applications that are recognized world-wide. We are seeking a motivated Software Engineer to join our team and contribute to the performance triage development and co-design of our software libraries in collaboration with our Hardware Architecture team. Join our team and gain exciting opportunities to work hands-on at every layer of NVIDIA's outstanding technology. What you will be doing: - Partner with multi-disciplinary teams to design, implement, and verify performance metrics for NVIDIA GPUs - Work on developing and improving methodologies for profiling data collection from GPUs - Define, invent, and improve our GPU profiling library with new features to allow NVIDIA's customers to extract the best performance out of their applications - Read and understand HW specs to design solutions based on it - Craft software unit level tests and framework ensuring the quality of the product - Work on supporting a variety of platforms ranging from super-computers to embedded systems What we need to see: - B.Tech. EE/CS or equivalent with 4+ years of experience, or M.Tech. with 2+ years of experience, or Ph.D. - Strong programming ability in C, C++, Python with proficiency in Data Structures and Algorithms - Solid understanding of Computer Architecture (e.g. x86, ARM CPUs, GPUs) and Operating System concepts - Knowledge of SW design principles, as that's a key as we scale! Ways to stand out from the crowd: - Experience in Device Drivers or System Software development - Knowledge of GPU APIs such as CUDA, OpenCL, OpenGL, Direct3D, Vulkan - Prior experience authoring developer tools, particularly for GPUs - Experience in performance analysis of GPU applications - Ability to read and write in Assembly language, especially for multi-processor architectures NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most dedicated and hard-working people in the world working with us. If the work described above excites you and you are up to the challenge, we want to hear from you. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people in multiple disciplines to help us accelerate the next wave of computing. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity, 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, disability status or any other characteristic protected by law.
Manager, Software Engineering - NCCL
We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication libraries like NCCL & NVSHMEM for Deep Learning and HPC. DL and HPC applications have a huge compute demand already 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! We are looking for a dynamic and technical leader for our China NCCL team. This is an outstanding opportunity to push the limits on the state-of-the-art and deliver platforms the world has never seen before. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: - Lead, mentor, and grow our China engineering team. Own the end-to-end execution spanning planning, prioritization, quality control and performance. - Interact with customers and researchers to understand their use cases and requirements. Collaborate with engineering, program and product management, and partners to define the product roadmap. - Contribute to feature design and implementation. - Continuously review and identify improvement opportunities in established processes, infrastructure, and practices to ensure the teams are accomplishing work in the most efficient and transparent manner. What we need to see: - 10+ overall years of experience in the software industry with 4+ years of management experience. - Bachelors, Masters, or Ph.D. in CS, CE, EE (related technical field) or equivalent experience. - Specialization in systems software, communication runtimes, or high performance networking. Proven success in managing several complex initiatives or products through the full product life cycle. - Strong understanding of computer systems architecture, networking technologies (RDMA, RoCE, Ethernet, EFA, InfiniBand) and topologies, operating systems principles (aka systems software fundamentals), HW-SW interactions and performance analysis/optimizations. - Hands-on C/C++ programming and debugging skills in Linux. - Experience balancing multiple projects with competing priorities. Flexibility to work and communicate effectively across different teams and timezones. Ways to stand out from the crowd: - Active user or developer of NCCL! - Customer engagement experience in this space. - Experience with parallel programming models (MPI, SHMEM) and at least one communication runtime (MPI, NCCL, NVSHMEM, NIXL, OpenSHMEM, UCX, UCC). - Experience with programming using CUDA, MPI, OpenMP, OpenACC, pthreads. - Knowledge of HPC and ML/DL fundamentals. Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, vLLM, SGLang, TRT-LLM, etc.
Senior Solutions Architect - Deep Learning
We are now looking for a Solution Architect - Deep Learning based in Israel. The individual will collaborate with brand-new Agentic and Physical AI tools alongside Machine learning, Deep Learning, and Data analytics to improve workflows and develop groundbreaking solutions. What You'll Be Doing: - Assisting field business development in guiding the customer through the sales process for GPU Computing products, owning the technical relationship and assisting the customer in building innovative solutions based on NVIDIA technology. - Be a motivating leader in integrating NVIDIA technology into HPC architectures to support scientific and engineering applications. - Be an internal champion for Deep Learning and Data Science among the NVIDIA technical community. - Develop demo solutions and showcase to the AI ecosystem. What We Need To See: - B.sc or M.sc in Engineering, Mathematics, Physics, or Computer Science or equivalent experience - 5+ years of experience in software development or extensive data analytics, CUDA experience highly desirable. - Experience working with modern Deep Learning software architecture and frameworks including PyTorch, VLLM, Triton - Proven Exposure to GPU technology and CUDA programming - Demonstrable experience in strategy, research, communications. - Capable of working in a constantly evolving environment without losing focus. - Committed with strong analytical and problem solving skills. - Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects. - Direct experience participating in communities (expertly or as highly engaged developer). Ways To Stand Out From The Crowd: - Technical knowledge of developer digital platforms and their trends. - Experienced working with containers, Kubernetes and MLoPS tools - Exposure to C, C++ and Python. - Research background. - Good presentation skills NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most dedicated individuals in the world working for us. If you're creative and autonomous, we want to hear from you! deeplearning
Senior Mask Design Engineer - Hardware
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 take on, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. We would love to hear from you! We are looking for a Senior Mask Layout Design Engineer, someone who is excited to join a growing and dynamic group of diverse individuals responsible for contributing to our latest generation chiplet interface projects What you'll be doing: - Performing physical layout for mixed-signal functions like top level, high speed datapaths and high-speed clocking designs in state-of-the-art sub-micron CMOS technologies using Cadence tools. - You'll work closely with mixed-signal design engineers to customize designs for integration in VLSI products. - Take part in floor planning, custom layout and verifying against design rules and schematics. What we need to see: - Have a BSEE or equivalent experience. - Minimum of 8+ years industry experience in Mask and Layout Design. - Working independently on creating layout with excellent quality - Deep understanding and previous experience for FinFET technology is a must - You are an authority with Cadence custom circuit design tools - particularly virtuoso. - Able to handle fast-paced project and iterate quickly based on designer’s feedback - You can work effectively in a team, good interpersonal skills, enthusiasm, and positive energy. - Scripting languages like perl, python, skill etc.is a plus - Should have knowledge of DRC and LVS checking flows, ability to customize decks. 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 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 4, 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.
Tech Engagement Lead - Model Builder
NVIDIA is seeking a highly influential Generative AI Technical Engagement Lead to evangelize for, drive, and support the seamless adoption and accelerate the performance of NVIDIA's accelerated computing stack across critical AI model development initiatives with leading AI model builders. As a key technical driver, you will facilitate deep technical integration and deepen our collaboration around NVIDIA's pioneering hardware, systems, and software libraries within their core development pipelines. This role demands a leader who can operate strategically at the intersection of product vision, advanced technical execution, and high-level customer engagement, directly influencing model architecture optimization, training infrastructure investments, and ensuring the deployment of robust, scalable generative AI solutions that redefine the state-of-the-art. What You Will Be Doing: - Lead Technical Engagement: Engage with senior technical leaders and research teams at AI model builders. Optimize their workflows by leveraging NVIDIA's complete stack for their end-to-end generative AI workflows. Serve as a primary technical point of contact. - Drive Integration: Accelerate the technical integration of NVIDIA's core generative AI technologies. This includes NVIDIA GPU architectures, DGX systems, high-performance networking (InfiniBand), CUDA-X libraries, NeMo frameworks, and inference libraries like TensorRT. Integrate these into the training and inference pipelines of large model builders. - Strengthen Partnerships: Support and strengthen technical implementation plans with partner AI engineering and researchers. Define clear technical objectives, performance breakthroughs, and timelines. Align these with their long-term model development goals and NVIDIA's AI strategy. - Influence Product Roadmaps: Represent the software needs of large model builders to internal NVIDIA product and engineering teams. Contribute to product roadmap decisions by synthesizing findings from large-scale model training and inference environments. Identify cross-industry patterns and advocate for improvements to NVIDIA's core technologies. - Maintain Strategic Relationships: Conduct regular cadence meetings. Document insights, track progress, and provide consistent internal reporting on the adoption and impact of NVIDIA technologies. - Showcase Best Practices: Share standard methodologies for crafting and optimizing highly scalable generative AI model development pipelines across all stages. Focus on the context of large model development. - Stay Updated: Keep current with the latest NVIDIA hardware, libraries, and system updates. Proactively share relevant insights and optimizations with partner model development teams. What We Need To See: - B.S. degree or equivalent experience. - 7+ years of experience in technical product or engineering roles. Focus areas include AI/ML, high-performance computing, or distributed systems. Emphasis on core technology integration and partner collaborations is key. - Extensive experience working with or developing platforms that facilitate large-scale AI/ML training and inference workloads. This includes distributed systems, data infrastructure, and groundbreaking GPU cluster technologies. - Hands-on knowledge of large model architectures (e.g., Transformers, Diffusion Models). Familiarity with core deep learning frameworks (e.g., PyTorch, JAX), and NVIDIA AI acceleration libraries (e.g., CUDA, cuDNN, NCCL, TensorRT, NeMo). Understand techniques for model customization, distributed training, and inference orchestration. - Strong understanding of compute infrastructure environments. This includes GPU cluster management, high-speed networking, parallel file systems, and deployment across on-premise and cloud infrastructures. Possess specific understanding of how large model builders operate at scale. - Proven ability to communicate and influence senior leadership across engineering and research leaders at partner organizations. Link NVIDIA technology capabilities to crucial AI model development and business value. - Successfully navigated fast-paced environments, taking decisive action to achieve results. Especially valuable in AI research collaborations. - Skilled at connecting with engineers, researchers, executives, and multi-functional teams. Ways to Stand Out From The Crowd: - Hands-on experience with large language models (LLMs), diffusion models, distributed training frameworks, and advanced optimization techniques. Ability to prototype quickly and integrate into model development pipelines. - Influence complex product and research decisions by nurturing positive relationships and understanding model builder needs. - Eager drive, strategic curiosity. Anticipate market trends in AI, shape NVIDIA's roadmap, and champion innovation. Understand the large model builder landscape. - Act as a technical advocate for NVIDIA GPU systems and software stack within assigned large model builder partners. Showcase its technical capabilities and strong value proposition. - Understanding of large-scale system performance optimization, container orchestration (e.g., Kubernetes), and Cloud Native technologies for AI workloads. Join NVIDIA at a crucial time as we pioneer Generative AI growth. We are in the infancy stage of building and scaling our Generative AI business for large model development. This role offers a unique opportunity to join this rapid expansion. NVIDIA's hardware, systems, and software libraries are at the heart of this growth. They empower large model builders to revolutionize their operations with powerful AI capabilities. This is your chance to be a key member of a team that will shape the future of AI model development, working with the world's leading AI research labs and the most innovative technologies. Your contributions will directly impact the trajectory of our Generative AI success, making this an unparalleled opportunity for professional growth and significant impact. 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 4, 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 Compiler Engineer
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 looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community. What you'll be doing: Analyzing deep learning networks and developing compiler optimization algorithms. Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work. What we need to see: Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience 3+ years of relevant work or research experience in performance analysis and compiler optimizations. Ability to work independently, define project goals and scope, and lead your own development efforts. Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design. Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. Ways to stand out from the crowd: Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience. Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation. Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch. GPU kernel generation with high performance and fast build time. A track record of success in mentoring junior engineers and interns is a bonus. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 152,000 USD – 241,500 USD. 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. #deeplearning
ASIC Clocks Verification Engineer - New College Gr...
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 take on, 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. The GPU clocks group is looking for an exceptional ASIC Clocks Verification Engineer. The team is responsible for crafting all aspects of GPU clocking. The team collaborates with the front design team to understand the clocking requirements for the chip. The clocks team interacts with the floor-planning and back-end team to help craft the physical floorplan of the chip. The team explains the programming model to the SW team to come up with an efficient clock programming sequence. The team works with the silicon solution team to triage silicon or programming bugs in the lab. What you'll be doing: - As a Clocks team member, you will be collaborating with other architects, ASIC designers and verification engineers to verify high frequency clock structures. - Be able to engage with multiple teams and design the GPU clock structure to satisfy all the architectural constraints. - Your understanding of general verification principles will be valuable to verify the clocks design. - Together with other team members, we deliver clock information to SOC verification team, timing and DFT teams. You will use Perl to improve the productivity of the above teams. - Collaborate with Software and product group to debug GPU clock silicon bugs in our new products. - Understand and design clocking structures to overcome sub-micron design challenges. - You will also identify improvements in the current design and propose and implement new ways to improve the efficiency in the GPU clocking design. What we need to see: - A Master’s degree in Electrical Engineering (or equivalent experience). - Practical experience with SystemVerilog and Universal Verification Method (UVM). - Experience with Design Verification, Logic Design, and Logic Synthesis. - Strong coding skills in Python, Perl, or other industry-standard scripting languages. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you creative and autonomous? If so, 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 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 4, 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 Research Engineer - AI Coding Tools
NVIDIA's AI Developer Tools organization is seeking a Senior Research Engineer to join our Research team, where we build the AI coding agents, models, datasets, and evaluations at the heart of NVIDIA's strategy to put AI-powered coding tools in the hands of every CUDA developer. The AI coding space is moving faster than any of us have seen — products rise and fall in months — and we work on it from the epicenter: the company whose hardware most of the AI industry runs on. Our team is small, in-person, and high-velocity. We prototype and ship novel coding agents, fine-tune and evaluate code LLMs, publish benchmarks like ComputeEval, and contribute datasets that feed NVIDIA's Nemotron foundation models. We make NVIDIA's core developer tools — including Nsight Compute and Nsight Systems — first-class citizens for AI agents through MCP servers and Agent Skills. The space shifts every few weeks, and we move with it. In this role, you'll bring applied AI research depth to a team that values shipping as much as experimentation. You won't be filling a narrow gap — you'll pick up significant projects across our portfolio, help set direction on new ones, and partner closely with product teams turning our research into features used by NVIDIA developers and external customers. For experienced AI-for-code practitioners who want to do frontier applied work with the stability and resources of NVIDIA behind them, this is a rare seat. What you'll be doing: - Build and improve novel coding agents that help NVIDIA developers write, optimize, and maintain CUDA code — and that work alongside other AI agents in the developer's workflow - Design and ship evaluations, including extensions of our public ComputeEval benchmark, that measure what really matters in AI-powered CUDA development - Fine-tune and specialize code LLMs, and partner with the Nemotron team on the datasets and evaluations that feed NVIDIA's foundation models - Develop Agent Skills, MCP servers, and other tool-use interfaces that make NVIDIA's developer tools (Nsight Compute, Nsight Systems, and more) first-class for AI agents - Generate, curate, and validate synthetic training and evaluation data for CUDA programming - Deliver "net new knowledge" to frontier LLMs through RAG and skill-based systems that keep models current with NVIDIA's fast-moving software stack - Collaborate with partner product teams to turn research prototypes into shipping features used inside NVIDIA and by external customers What we need to see: - B.S. in Computer Science or related technical field or equivalent experience (M.S. or Ph.D. a plus) - 12+ years of industry experience in applied AI/ML, with meaningful recent work in the AI-for-code space — coding agents, code LLMs, AI developer tools, or adjacent systems - Strong proficiency in Python and sound software engineering practices - Hands-on experience fine-tuning or evaluating LLMs, with appropriate humility about the complexity of training and data work - Fluency with the systems side of LLM-powered agents, including practical concerns like context management, prompt caching, tool-use design, MCP, and Agent Skills - Experience designing or contributing to rigorous evaluations for code generation or agentic systems - Track record of shipping — taking work past the prototype stage and into the hands of real users - Comfortable in a small, collaborative, in-person team with fast direction changes and little process overhead Ways to stand out from the crowd: - Public contributions in the AI-for-code space — open-source agents or tools, widely-used benchmarks, influential papers, or blog posts with demonstrated real-world impact - Experience building coding agents or code LLMs that real users rely on every day - Familiarity with CUDA or other GPU programming, and/or with NVIDIA profiling tools (Nsight Compute, Nsight Systems) and libraries (cuDNN, cuBLAS, Thrust, CUB) - Experience with synthetic data generation and quality validation for code - Track record of zero-to-one product work, or work inside a recently-rebooted org with a strong mandate and customer pull With competitive salaries and benefits, 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 an applied AI researcher or engineer who wants to ship AI coding tools from the epicenter of the AI industry, and you thrive in a small, in-person team with a clear mandate, this is the role 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 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 May 4, 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 Systems Software Engineer - Advanced Techno...
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, join our diverse team today! The Advanced Technology Group is looking for a highly motivated Senior Systems Software Engineer to join our group. Do you have a proven software development background in advanced computational methods for semiconductor manufacturing and design? Are you seen as a technical leader and an industry expert in several of the underlying fields, such as massively distributed computing, computational geometry, diffractive optics, and artificial intelligence? If yes, then we’d love to hear from you! The job requires creating strategy, driving industry-leading innovation, and working in lean teams to realize these strategies, from invention to production. This role will be located in Hillsboro, Oregon. What you'll be doing: - Working with some of the best technologists in the world to build industry-leading advanced computational methods for semiconductor manufacturing and design. - Exploiting the potential of the GPU to dramatically accelerate these software solutions. - Ultimately, keeping the cadence of semiconductor innovation alive by accelerating semiconductor yield and time to market. What we need to see: - MS (PhD preferred) in Computer Science or Engineering or equivalent experience. - 5+ years of research/industry experience - A track record of innovation, for example by the invention of computer algorithms. - Experience in developing and delivering complex software solutions for enabling or improving semiconductor fabrication and design. - A track record of scaling up software to a level that efficiently utilizes millions of compute hours, and processes petabytes of data. Ways to stand out from the crowd: - Deep understanding of technology and passionate about what you do. - Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment. 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. It’s not just technology though! It is our people, some of the brightest in the world, and our company and diverse culture that make NVIDIA one of the most fun, innovative and dynamic places to work in the world! At the center of NVIDIA's culture are our core values - like innovation, excellence and determination, and one team - that guide us to be the best we can be. 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 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 5, 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 Product Manager, Local AI and Agents for En...
We are looking for a technical and hands-on Product Manager to lead our product efforts for local AI on Linux and developers. Client AI is the technology platform on top of NVIDIA's client hardware — GeForce RTX, RTX PRO, DGX Spark, DGX Station, and N1X — that enables AI and agents, content creation, and developer workflows. This Product Manager will define how developers, researchers, and enterprise teams build, run, and deploy AI on NVIDIA client platforms running Linux, with a strong focus on enterprise. Generative AI is moving from the cloud to the workstation and the edge. Developers want to prototype, fine-tune, and run frontier models locally. Enterprises want to deploy agents against their private data on-prem. Inference stacks like vLLM, SGLang, TensorRT-LLM, and PyTorch are becoming the default runtime for these workflows. This Product Manager will help NVIDIA win the Linux side of this shift — making our client platforms the best place to build and run modern AI. What you'll be doing: - Define and lead the enterprise agent use case — understand how enterprises deploy agents on-prem, what they need from the platform, and where NVIDIA should invest. - Collaborate with Product Managers that are working on cloud inference backends (vLLM, SGLang, TensorRT-LLM, and PyTorch) to drive and prioritize requirement for local AI. - Own the product strategy and roadmap for the Linux developer experience on NVIDIA client platforms (DGX Spark, DGX Station, RTX PRO workstations, RTX Spark). - Research the developer and enterprise AI ecosystem: interview customers, build personas and user journeys, and map workflows across training, fine-tuning, inference, and agent deployment. - Work hands-on with the latest models, frameworks, and agent tooling so you can represent the developer's point of view in every decision. - Lead cross-functional teams — engineering, DevRel, marketing, partnerships — to ship features and grow adoption. - Influence NVIDIA's GPU, system, and software roadmaps based on what Linux developers and enterprise AI teams actually need. - Build product positioning, technical demos, and sales and partner enablement material for a developer audience. What we need to see: - 8+ years of product management experience, with meaningful time on AI/ML, developer tools, or infrastructure products. - First-hand experience as a developer or engineer — you have shipped code in production and can debug a CUDA, PyTorch, or Docker issue alongside an engineer, not just manage around it. - Deep familiarity with modern AI workflows: training and fine-tuning, inference serving, agent frameworks, RAG pipelines, and evaluation. - Working knowledge of at least one major inference backend (vLLM, SGLang, TensorRT-LLM, or PyTorch-based serving). - Fluency in Linux as a development and deployment environment. - Strong written communication and the ability to translate technical depth for both engineers and executives. - Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience. Ways to stand out from the crowd: - Prior role as an AI/ML engineer, inference systems engineer, or application developer building with LLM APIs and agent frameworks (LangChain, LlamaIndex, MCP). - Experience with model optimization — quantization, distillation, speculative decoding, KV-cache strategies. - Hands-on with CUDA, Triton, or low-level GPU programming. - Background in enterprise software, on-prem deployments, or private AI. - Open-source contributions to AI/ML, inference, or agent projects. 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 168,000 USD - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 8, 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.
Machine Learning Applications and Compiler Enginee...
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! 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: - Pursuing or recently completed a MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience. - Possess software engineering background with familiarity 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. - 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. 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 105,000 CAD - 155,000 CAD for Level 2, and 135,000 CAD - 185,000 CAD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
Principal Partner Enablement Product Manager, AI I...
This Principal Partner Enablement Product Manager, AI Infrastructure owns adoption and alignment for our ODM partners delivering data center solutions to customers. The person in this seat represents our ODM to the DSX suite ecosystem. They will position the primary DSX composition, help partners build accurately, and keep them aligned with the DSX architecture during delivery. Equally important, the person serves as the structured voice of the ODM for our in-house DSX solution and data center engineering teams. They bring real-world partner feedback to build the foundational DSX Plan of Record. The Principal Partner Enablement Product Manager, AI Infrastructure role focuses on three main missions within the partner ecosystem. First, the role leads positioning and enablement by introducing and promoting the DSX platform to ODM partners. This ensures successful design-in and ongoing adoption of the data center blueprint. Second, it supports partners throughout delivery, keeping them aligned as ODMs complete AI Infrastructure data center programs for their customers. Third, it acts as an important feedback and innovation channel that transforms real-world partner insights into actionable suggestions. These suggestions guide product and engineering teams to improve the foundational product strategy. If you are passionate about driving new technologies to market and thrive in a fast-paced environment then this is the perfect job for you. Does this sound like your dream job? Come show us what you got! What You'll Be Doing: - Deeply understand the central DSX platform and translate it into compelling, accessible positioning for ODM engineering and business teams - Lead DSX onboarding and build-in engagements with ODM partners — architecture reviews, reference build adoption, and blueprint compliance - Maintain continuous ODM alignment following the DSX data center framework throughout the delivery lifecycle, identifying and addressing deviations before they reach the customer - Serve as the primary interface between ODM partners and the internal DSX product team. Aggregate and clearly communicate partner feedback on stack usability, deployment gaps, and real-world constraints. - Bring ODM field findings clearly and credibly into the core POR process of DSX. Advocate for product optimizations that reflect what partners encounter when deploying mid to senior-level roles at scale. - Develop and sustain constructive connections with leadership in ODM engineering, ensuring they regard DSX as an essential investment instead of a mere compliance obligation - Support the development of enablement materials — technical briefs, build guides, deployment playbooks — that make it easier for ODMs to adopt and stay on the DSX blueprint - Track and report ODM adoption depth, alignment with the blueprint, and feedback themes to DSX leadership What we need to see: - 15+ years in product management, technical enablement, or solutions engineering. This includes significant experience working with or inside ODM partners on data center or computing infrastructure programs. - Hands-on experience with AI Infrastructure delivery from the ODM side — understands the design-in process, program pressures, and how architectural decisions get made - Demonstrated ability to enable external partners to adopt a complex technical stack, including design-in programs, architecture reviews, or blueprint compliance - Prior experience as a conduit between external partners and internal product teams — comfortable synthesizing field feedback into actionable product input - Strong grasp of data center architecture and the infrastructure layers that make up a full DC deployment - Technically proficient enough to engage credibly with ODM hardware and systems engineers on DSX architecture, reference builds, and deployment blueprints - Strong product instincts — able to distill qualitative ODM feedback into clear, prioritized input for the core DSX POR - Excellent written and verbal communication; able to position the DSX stack at both executive and engineering levels within ODM organizations - A Bachelor's degree or equivalent experience, or a Master's degree or similar experience in Electrical Engineering, Computer Engineering, Mechanical Engineering, or a related area Ways to stand out from the crowd: - Mandarin proficiency (spoken and written) is a plus — given the depth of daily engagement with original device manufacturers’ engineering and leadership teams - Prior experience working at or embedded with a Tier 1 ODM on a DC infrastructure program - Familiarity with DSX architecture, internal build review processes, and how the DSX is structured. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 240,000 USD - 379,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 8, 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 DL Algorithms Engineer - Inference Performa...
We are looking for a Senior DL Algorithms Engineer for LLM/Omni model optimizations! Seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning workloads. If you are unafraid to work across all layers of the hardware/software stack from GPU architecture to Deep Learning Framework to achieve peak performance, we want to hear from you! This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution. What you will be doing: - Enable and optimize state-of-the-art open models (like Nemotron and Cosmos) on NVIDIA’s accelerated inference SW stack. - Contribute new features, fix bugs and deliver production code to open-source frameworks like TRT-LLM, vLLM, SGLang, FlashInfer, etc. - Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance. - Benchmark state-of-the-art offerings and perform competitive analysis for NVIDIA’s SW/HW stack. - Co-design with partner teams to develop the next generation of AI models and services. What we want to see: - PhD in CS, EE or CSEE or equivalent experience. - 3+ years of experience. - Strong background in deep learning and neural networks, in particular inference. - Experience with performance profiling, analysis and optimization, especially for GPU-based applications. - Proficient in PyTorch or equivalent frameworks for AI, or HPC-heavy application development. - Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. Ways to stand out from the crowd: - Proven experience with processor and system-level performance optimization. - Deep understanding of modern LLM/Diffusion architectures. - Strong fundamentals in algorithms. - GPU programming experience (CUDA or OpenCL) is a strong 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 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 9, 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 Mask Design Engineer - Hardware
Are you a Mask Layout Design Engineer? We are looking for a Senior Mask Layout Design Engineer, someone who is excited to join a growing and multifaceted group of diverse individuals responsible for handling meaningful high-speed mixed-signal circuit designs. 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 take on, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. We would love to hear from you! What you'll be doing: - Performing physical layout for mixed-signal functions like PLL's, high speed SerDes, Analog to Digital converters, ESD structures designs in innovative sub-micron CMOS technologies using Cadence tools. - You'll work multi-functional with ASIC and mixed-signal engineers to customize designs for integration in VLSI products. - Take part in floor planning, custom layout and verifying against design rules and schematics. What we need to see: - Have a BSEE or equivalent experience and minimum of 8+ years industry experience. - Deep understanding of analog circuit layout concepts in submicron CMOS technologies. - You are an authority with Cadence custom circuit design tools - Experience running and debugging with verification tools such as Dracula, Hercules, Calibre, and Primeyield. - You are able to work optimally in a team, good interpersonal skills, passion and positive energy. - Proficient in scripting languages like perl, python, skill etc. - Should have knowledge of DRC and LVS checking flows, ability to customize decks. 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. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 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 Performance Architect
We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking outstanding Performance Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications. Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field! What you’ll be doing - Design and evaluate hardware architectures to improve performance, efficiency, and scalability of production AI workloads. - Analyze and optimize large-scale deep learning workloads, especially LLM inference/training in real-world deployments. - Build and use performance and power models (Python/C++) to drive architecture and product decisions. - Identify and resolve system bottlenecks across compute, memory, and interconnect. - Evaluate PPA trade-offs and guide feature prioritization for next-generation GPU/ASIC designs. - Partner closely with software, systems, and product teams to align hardware capabilities with workload requirements. What we need to see: - MS or PhD in a relevant field (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience. - 5+ years of hands-on experience in GPU/ASIC architecture, parallel computing, or system performance engineering. - Experience with deep learning workloads in production environments (training and/or inference). - Proficiency in Python and C++ for building performance models, simulators, or analysis tools. - Solid understanding of system architecture: memory hierarchy, data movement, and scalability. - Prior experience debugging, profiling, and performance tuning on real systems. - Ability to work across team and drive decisions in fast-paced product environments. Ways to stand out from the crowd: - Experience translating workload behavior into concrete hardware or system-level improvements. - Practical experience with LLM inference optimization: batching, disaggregation, KV-cache management, latency/throughput tuning. - Familiarity with production inference systems (e.g., scheduling, multi-node scaling, resource utilization) 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 9, 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.
Machine Learning Applications and Compiler Enginee...
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! 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: - Pursuing or recently completed a MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience. - Possess software engineering background with familiarity 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. - 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. 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 135,000 CAD - 185,000 CAD for Level 3, and 170,000 CAD - 220,000 CAD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
Senior Mixed Signal 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 creativity and intelligence. Make the choice and join us today! This is a dynamic team working with pioneering, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! We are looking for a senior engineer to be part of the mixed-signal design team building next generation NVLINK. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. What you'll be doing: - Develop and implement high speed electrical/optical interfaces and analog circuits. You will have hands on experience taking innovative integrated circuit designs at data rates of 25Gbps and higher from concept through silicon characterization. - Help by defining circuit requirements and complete design from schematic, layout, and verification to characterization. - Conduct schematic design of deep-submicron CMOS technologies using Spectre, Hspice or like. - Lead architecture, transistor design and verification using industry standard EDA tools such as Cadence virtuoso. - Optimize circuit to meet the specifications for system performance. - Work closely with layout engineers by providing detailed floorplan and guidance for matching and high-speed routings. - Provide support for post-silicon bring-up and debugging. What we need to see: - Master of Science or Ph.D. in Electrical Engineering, Computer Engineering or related field with strong analog design background (or equivalent experience) - 6+ years analog design experience - CMOS Analog / Mixed Signal Circuit Design Experience in deep sub-micron process (especially in FINFET) - Experience with design and verification tools (Cadence's IC design environment, analog circuit simulation tools like Spectre, HSpice, Finesim, XA) - Experience in crafting test bench environments for component and top level circuit verification - Behavioral modeling of analog and digital circuits - Strong debugging and analytical skills - Analog simulation for noise analysis, loop stability analysis, ac/dc/tran analysis, monte-carlo, etc. - Strong interpersonal skills and ability & desire to work as a phenomenal teammate are huge 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 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 9, 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 Solutions Architect, Autonomous Driving - G...
NVIDIA is building the world’s leading AI company, and we are looking for an expert AV and GenAI Solutions Architect to help assist customers with adoption of NVIDIA's full-stack technologies as well as building and deploying solutions around Generative AI and Physical AI and other related GPU-accelerated technologies in which intelligent agents can learn, reason, and interact the world. As part of the Automotive Solutions Architecture team, we work with some of the most innovative accelerated computing platforms focused on the development and test of autonomous vehicles, in-vehicle AI assistance, and ride sharing algorithms among other things. A Solutions Architect is the first line of technical expertise between NVIDIA and customers so you will engage directly with developers, researchers, and visionary scientists at some of the most strategic customers as well as work directly with business and engineering teams on product strategy as it pertains to these customers. Join us in this exciting endeavor! What you'll be doing: - Engage with customers to help them scope and develop solutions for building AV perception and planning models and pipelines, simulations, synthetic data generation, and software in the loop testing, AI enhanced manipulation and navigation workflows using NVIDIA's Physical AI platforms and CUDA-X libraries. - Provide hands-on technical mentorship to partners and customers on Nvidia GenAI stack. Guide customers to develope and deploy Agentic AI workflows on our platforms, quantifying the benefits of our accelerated computing software and hardware. - Partner with Sales, Engineering, Product and other Solution Architect teams to drive NVIDIA full stack adoption. Develop a deep understanding of customer workflows and requirements, lead proof-of-concepts evaluations and provide internal feedback to drive continuous product improvements. - Build collateral (notebooks, github repos, demos, etc.) applied to workflows such as AV and GenAI data curation, model training and validations, LLMs, VFMs, video encoding/decoding, etc. What we need to see: - Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience. - 8+ years of hands-on experience in a technical AI role, with a strong emphasis on AV End-to-End models and GenAI model development. - Experience writing production codes in Python, or C++ and proficiency with Linux. - Hands-on experience with DevOps tools such as GitLab, Docker, and Kubernetes. - Strong understanding of AV systems (Sensors, dynamics, perception, prediction, planning, control). - Experience with DL and RL algorithms and frameworks such as PyTorch. - Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales and marketing teams). - Effective verbal/written communication, and technical presentation skills. - Self-starter with a vision for growth, real passion for continuous learning and sharing findings across the team. Ways to stand out from the crowd: - Experience with AV sensors, data curation pipelines, world models, simulations workflows and tools e.g., Carla. - Experience with Agentic AI frameworks, tools, and protocols like LangChain, LangGraph, MCP or equivalent experience. - Understand computational characteristics of Multimodal LLMs, VLMs, DiT, etc. - Experience in deploying LLM models at scale on mainstream cloud providers (e.g., AWS, Azure, GCP). - Proven track record to profile and optimize inference latency and throughput, memory and I/O utilization. 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 9, 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.
Applied AI Engineer - DFT Methodology
NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work , to amplify human creativity and intelligence. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our diverse team and see how you can make a lasting impact on the world! Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification, and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: - As an integral member in our team, you will work on exploring Applied AI solutions for DFX and VLSI problem statements. - Architect end-to-end generative AI solutions with a focus on LLMs, RAGs & Agentic AI workflows. - Work on deploying predictive ML models for efficient Silicon Lifecycle Management of NVIDIA's chips. - Collaborate closely with various VLSI & DFX teams to understand their language-related engineering challenges and design tailored solutions. - Partner closely with cross-functional AI teams to provide feedback and contribute to the evolution of generative AI technologies. - Work closely with DFX teams to integrate Agentic AI workflows into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies. - Define how data will be collected, stored, consumed and managed for next-generation AI use cases. - You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: - BSEE or MSEE from reputed institutions with 2+ years of experience in DFT, VLSI & Applied Machine Learning - Experience in Applied ML solutions for chip design problems - Significant experience in deploying generative AI solutions for engineering use cases - Good understanding of fundamental DFT & VLSI concepts - ATPG, scan, RTL & clocks design, STA, place-n-route and power - Experience in application of AI for EDA-related problem-solving is a plus - Excellent knowledge in using statistical tools for data analysis & insights - Strong programming and scripting skills in Perl, Python, C++ or TCL desired - Strong organization and time management skills to work in a fast-pace multi-task environment - Self-motivated, independent, ability to work independently with minimal day-to-day direction - Outstanding written and oral communication skills with the curiosity to work on rare challenges NVIDIA offers highly competitive salaries and a comprehensive benefits package. 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 growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you! LI-Hybrid
Solutions Architect - AI Technology Centre
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you'll be doing: As a Solutions Architect in NVIDIA AI Technology Center (NVAITC), you will be leading the way in AI research and application. You will: - Serve as a research & engineering subject matter expert (SME), driving internal and external collaborations with academia and industry. - Serve as the technical expert for NVIDIA technologies, in particular ALCHEMI and more broadly, our CUDA-X libraries. - Keep up to date on the latest AI advances in Chemistry and Materials Science, including atomistic simulation, machine learning interatomic potentials (MLIPs), quantum chemistry, and generative models for molecules and materials - Lead and mentor junior technical members, encouraging a collaborative and inclusive environment. - Collaborate with the management team to develop and implement strategic engagements and projects involving institutes of higher learning (IHLs), industry, and government, ensuring seamless delivery and implementation. - Play a key role in NVIDIA’s global initiative to foster accelerated AI throughout the ecosystem by facilitating and supporting workshops, symposiums, and technical sharing sessions. - Mentor collaborators, interns, and students, providing mentorship and skills training to successfully implement AI projects. - Develop NVIDIA technology-related tutorials, demos, and workshop materials, showcasing our world-class innovations. What We Need To See: - Demonstrated 5+ years of experience ‘AI for Chemistry and Materials Science’ and familiarity with NVIDIA technologies (e.g., ALCHEMI, cuEquivariance, cuEST). - A PhD or equivalent experience in Computational Chemistry, Materials Science and Engineering, Computer Science, or related research domains. - A proven history of guiding and assisting research & engineering projects. - Technical mentoring experience in areas such as research/engineering projects. - Experience in AI ecosystem development and collaboration initiatives. - Proficiency in coding with Python and using AI/ML libraries such as PyTorch. - Excellent time management skills, self-motivation, and the ability to work both independently and within a team. - Effective communication skills, enabling you to articulate complex concepts clearly and concisely. 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 Deep Learning Tools Engineer – CUDA Tile
NVIDIA is building advanced compiler technologies to accelerate AI workloads, and we are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time. Do you want to help drive the performance of next-generation compilers? Are you excited by how GPU performance powers breakthroughs in deep learning, autonomous systems, and high-performance computing? We are seeking a talented Deep Learning Compiler & Tools Engineer focused on CUDA Tile (Performance & Infrastructure) to join our team. You will collaborate closely with compiler developers, infrastructure providers, and hardware teams to build systems that track, analyze, and improve performance across rapidly evolving AI workloads. If you're passionate about performance, systems, and building infrastructure that drives real-world impact, we want to hear from you. What You’ll Be Doing: - Design and develop performance testing frameworks for deep learning compilers and workloads - Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes - Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads - Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities - Partner with compiler and architecture teams to debug and resolve performance issues - Develop tools and dashboards for performance visualization, reporting, and insights - Enable scalable testing across diverse GPU systems and environments - Improve infrastructure to ensure reliable, reproducible, and high-signal performance data What We Need to See: - BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field - 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization - Strong programming skills in Python (C++ is a plus) - Experience with CI/CD systems and automation frameworks - Familiarity with hardware-aware performance analysis (GPUs, accelerators, or similar systems) - Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT - Background in data analysis, profiling, and regression tracking - Ability to debug complex system-level issues across software and hardware layers Ways to Stand Out from the Crowd:: - Experience with GPU performance analysis and optimization - Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow) - Experience building performance dashboards and large-scale telemetry systems - Familiarity with hardware/software co-design or low-level performance tuning - Experience with distributed testing infrastructure or large-scale benchmarking systems With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the most desirable employers in the technology industry. Our teams are tackling some of the most challenging problems in AI, deep learning, and accelerated computing. 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. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 10, 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
Research Scientist
NVIDIA is searching for outstanding AI researchers to join the NVIDIA Research Singapore team. We are dedicated to the development and optimization of GPU-accelerated efficient AI computing, covering language model, visual generation, and robotics. We focuses on pushing the boundaries of generative AI by designing models that are not only powerful but also efficient in terms of computational resources. You will be part of an amazing collaborative research team that consistently publishes at the top venues in machine learning, robotics and computer vision. Your contributions have the chance to create real impact on our products. What you'll be doing: - Research, design and accelerate novel generative AI models - Publish original research - Collaborate with other team members and teams - Mentor interns - Speak at conferences and events - Transfer technology to product groups - Collaborate with external researchers What we need to see: - Excellent knowledge of LLM and foundation models - Publication at leading conferences (ie. CVPR, ICML, ICLR, ICCV, NeurIPS, etc) - 2 years of experience. Bachelor, master, or PhD degree in computer science or electrical engineering with strong research track records. - Excellent programming skills in some rapid prototyping environment such as Python; C++ and parallel programming (e.g., CUDA) is a plus - Knowledge of common machine learning frameworks, such as PyTorch - Excellent communication skills NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. Looking forward to hear from you.
AI Research Scientist
NVIDIA is searching for outstanding AI researchers to join the NVIDIA Research Singapore team. We are dedicated to the development and optimization of GPU-accelerated efficient AI computing, covering language model, visual generation, and robotics. We focuses on pushing the boundaries of generative AI by designing models that are not only powerful but also efficient in terms of computational resources. You will be part of an amazing collaborative research team that consistently publishes at the top venues in machine learning, robotics and computer vision. Your contributions have the chance to create real impact on our products. What you'll be doing: - Research, design and accelerate novel generative AI models on NVIDIA GPUs - Publish original research - Collaborate with other team members and teams - Mentor interns - Speak at conferences and events - Transfer technology to product groups - Collaborate with external researchers outside NVIDIA What we need to see: - Excellent knowledge of LLM and foundation models - Publication at leading conferences (ie. CVPR, ICML, ICLR, ICCV, NeurIPS, MLSys, etc) - 4 years of experience. - PhD degree in computer science or electrical engineering with strong research track records. - Excellent programming skills in some rapid prototyping environment such as Python; C++ and parallel programming (e.g., CUDA) is a plus - Knowledge of common machine learning frameworks, such as PyTorch - Excellent communication skills NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. Looking forward to hear from you
Senior Perception Engineer - Autonomous Vehicles
Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA’s autonomous driving solutions. As a member of our perception team, you will work on building world-class 3D obstacle perception solutions based on multi-sensor fusion, including cameras, ultrasonic sensors, and radar, to estimate high-resolution reconstruction of the world. The primary approach will be deep learning. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime. What you’ll be doing: - Perception experts with application focus will be on multi-sensor fusion based deep learning model development for obstacle perception/fusion in complex driving environments. - Applied research and development of innovative deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios. - Identify and analyze the strength and weakness of the developed 3D obstacle perception solutions using large scale benchmark data (both real and synthetic) and improve them iteratively through KPI building and optimization. This includes careful data verification, model architecture design, understanding details of loss function engineering, and being capable of finding detailed ML bugs and iterating toward perfection. - Productize the developed 3D obstacle perception solutions by meeting product requirements for safety, latency, and SW robustness, with a strong emphasis on production deep learning model development. - Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy. Efforts will include data collection prioritization and planning, labeling prioritization, so that value of data is maximized. What we need to see: - 10+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch). - Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly in high-resolution world reconstruction. - Proven experience in production deep learning model development, including careful data verification, model architecture design, loss function engineering, and debugging ML models. - Experience in data-driven development and collaboration with data and ground truth teams. - Strong programming skills in python and/or C++. - Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other. - BS/MS/PhD in CS, EE, sciences or related fields (or equivalent experience) Ways to stand out from the crowd: - Experience on end-to-end deep learning model development is a plus. - Proven expertise in developing perception solutions for autonomous driving or robotics using deep learning with multi-sensor input. - Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications. - Good understanding of fundamentals of 3D computer vision, camera calibrations including intrinsic and extrinsic, and sensor fusion principles. - Experience with development in CUDA language. The ability to implement CUDA kernels as part of training or inference pipelines. 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 10, 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 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 6+ 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 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 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 10, 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.
Applied Deep Learning PhD Research Intern, Reinfor...
We are looking for PhD research interns excited to advance the next generation of large language models through reinforcement learning. Our applied deep learning research team at NVIDIA has helped pioneer projects such as Megatron, MT-NLG, and DLSS. We build state-of-the-art foundation models and develop new methods to improve their reasoning, alignment, reliability, and ability to solve real-world tasks. This internship will focus on algorithmic research at the intersection of reinforcement learning and large language models. You will design, implement, and evaluate new RL-based methods for improving LLM behavior, with a strong emphasis on hands-on experimentation and rapid prototyping at scale. What you will be doing: - Develop and prototype reinforcement learning algorithms for large language models - Explore methods for improving reasoning, alignment, instruction following, and multi-turn interaction - Design experiments to evaluate model behavior, robustness, hallucination, and task performance - Implement research ideas in Python and PyTorch, and run experiments on large-scale GPU clusters What we need to see: - Pursuing a PhD in AI, ML, CS, CE, EE, Math, Physics, or a related field - Strong background in reinforcement learning and natural language processing - Excellent programming skills, especially in Python - Experience with deep learning frameworks such as PyTorch - Comfort with experimental research, debugging models, and working with large-scale training pipelines Ways to stand out from the crowd: - Publications or open-source contributions in RL, LLMs, alignment, reasoning, or post-training - Experience with RLHF, RLAIF, policy optimization, reward modeling, or agentic LLM systems - Strong intuition for both algorithms and large-scale implementation If you are excited about using reinforcement learning to make language models more capable, reliable, and useful, this team could be a great fit. Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 30 USD - 94 USD. You will also be eligible for Intern benefits . Applications for this job will be accepted at least until May 10, 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 Mixed Signal Design Engineer
We are looking for a Senior Mixed-Signal/Analog/IO Circuit Design Engineer – someone who is excited to join a growing group of diverse individuals responsible for handling challenge high-speed memory interface designs. 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 pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. What you'll be doing: - Mixed-Signal/Analog circuit design for High Speed Memory I/O Interfaces - Solve challenge of circuit designs in deep submicron CMOS FinFET processes - Take designs through productization and be involved in all stages of development - Work with multi-functional teams to optimize the designs What we need to see: - Advanced High-Speed Design Expertise: 5+ years of proven experience in high-speed memory (LPDDR, DDR, GDDR, HBM) or SerDes design, underpinned by a BSEE or MSEE and a deep understanding of system-level timing budgets and specifications. - FinFET Circuit Mastery: In-depth technical command of deep submicron CMOS FinFET processes, with the ability to navigate complex circuit design challenges and implementation nuances. - Reliability & Physical Integrity: Comprehensive knowledge of device reliability, ESD, and Latch-Up requirements, including the ability to supervise layout development to ensure strict adherence to these critical rules. - Full-Flow Tool Proficiency: Expert-level command of Cadence custom design environments and industry-standard simulators (Hspice, XA, FineSim, Spectre), with a working knowledge of Verilog, Nanotime, or Matlab. - Silicon-to-System Perspective: Ability to bridge the gap between die and system, offering insights into package substrate design, board-level constraints, and Power Delivery Network (PDN) analysis. - Collaborative Leadership: A proactive teammate with strong interpersonal skills, capable of mentoring junior engineers and performing hands-on validation using high-end lab test and measurement equipment. 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, gender, 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.
Software Development Engineer in Test - SDET
NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you. We are now looking for a Software QA Development Engineer; you will collaborate with multi-functional groups. SWQA Developer Engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA Engineer can improve productivity or optimize test plan. As a SWQA Developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What you’ll be doing: - Review product requirements and develop test matrix. - Build test plan, design test case, execute and report test progress, bugs, and results to management. - Automate test cases and assist in the architecture, crafting and implementing of test frameworks. - Manage bug lifecycle and co-work with inter-groups to drive for solutions. - In-house repro and verify customer issues/fixes. What we need to see: - BS or higher degree or equivalent experience in CS/EE/CE plus equivalent with 3+ years QA experience. - Proficient in Unix/Linux and shell/python programming skills. - Rich experience in test cases development, tests automation in API/UI and failure analysis. - Solid experience with AI development tools, including creating test cases, automating test cases, and ensuring comprehensive code coverage, among other related tasks - Good knowledge and hands-on experience in model testing and LLM benchmarking - Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc. - Excellent communicator, fluent written and verbal English. - Good teamwork with ability to work independently. - Passion to learn new hardcore technology. Ways to stand out from the crowd: - Experience working with NVIDIA GPU hardware is a strong plus - Background in deep learning frameworks is a plus - Experience in parallel programming ideally CUDA/OpenCL is a plus
Senior Research-Ops & DevOps Engineer
Nvidia is looking for a Senior Software Engineer to join our Video/Multimedia Architecture & Algorithms (A&A) team — the people who build tomorrow’s NVENC and NVDEC, the dedicated video encode and decode engines that power streaming, cloud gaming, video conferencing and broadcast on every modern NVIDIA GPU. You will lead the infrastructure and operations for this group’s work. This includes setting up compute resources on-premises and in the cloud. You will develop distributed pipelines for large-scale regressions and experiments across hardware simulations and machine learning workloads. You will maintain the CI/CD and development environments. You will also transform one-off research workflows into reliable, repeatable, automated systems. This is a hybrid role — 4 days per week from the office. What You'll Be Doing - Work closely with our Architects and Algorithms Engineers to understand the needs and transform one-off research workflows into dependable, consistent, automated systems - Stand up and operate the compute the group runs on — on-prem GPU clusters, cloud bursts, queues, schedulers (Slurm / Kubernetes), container images, environments - Develop and build decentralized workflows for extensive regression testing and experiments across HW-simulations and ML workloads — and the dashboards that make sense of the results - Lead the team’s CI/CD plus the dev environments, container images and tooling everyone in the group lives in every day What We Need To See - B.Sc. in Computer Science or Electrical/Computer Engineering - 5+ years in a DevOps, SRE, MLOps, Research-Ops or platform-engineering role - Strong Linux fundamentals — shell, processes, networking, filesystems, systemd, performance tools - Strong hands-on experience in Python — confident writing production-quality code, not just scripts - Hands-on experience with at least one major Cloud ecosystem (OCI, AWS, Azure, GCP) and with Infrastructure as Code (Terraform, Pulumi or similar) - Containers and orchestration: Docker plus Kubernetes, and/or HPC schedulers like Slurm - Experience designing and bringing up CI/CD flows at scale (GitLab CI, GitHub Actions, Jenkins or similar) and operating distributed batch pipelines Ways To Stand Out From The Crowd - Familiarity with video compression / codecs (NVENC, NVDEC, FFmpeg, GStreamer) - GPU-aware infrastructure experience: CUDA toolkit installs, driver versioning, MIG, NCCL - Reading-level comfort with C++ — enough to debug a build or trace a benchmark issue into the codec stack - Observability experience — Prometheus, Grafana, OpenTelemetry, structured logging 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! NVIDIA is committed to fostering 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.
Solution Architect, Generative AI
NVIDIA is a world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, NVIDIA has been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the world's hardest problems. We are now looking for a Solution Architect to work with enterprise companies in Japan and partners , promoting the adoption and providing technical support to enable them to use our portfolio of GPU-accelerated computing solutions—including machine learning, deep learning, and especially generative AI . In Japan, the development of sovereign AI and agent-based systems using it is rapidly progressing. We are looking for people who are interested in pre-sales and technical support activities involving support and proposals for those model training and deployment. W e need a passionate, hard-working, and creative individual who has the skills and aims to work in a fast-evolving technological environment that is always on the cutting edge of AI and Accelerated Computing. This individual is self-driven , excellent in communication and partnership, stays on top of tasks, mission focused and outcome oriented. What you'll be doing: - Develop and demonstrate solutions based on NVIDIA’s pioneering GenAI software and hardware technologies with a focus on inference. This may include advising our customer on agent-based system design and optimal models and infrastructure. - Work directly with key customers to understand their challenges and provide the best solutions based on NVIDIA products - You will drive sustainability by performing in-depth analysis and optimization to ensure the best performance and cost-effectiveness using the NVIDIA software platform. This includes transitioning pipelines to lower precision compute . - Drive pre-sales conversations, build architectures and demos to accelerate the customer AI journey based on NVIDIA products, and work closely with Sales Account Managers to secure design wins. - Create or run Proofs of Concept and demos that require presentation skills, the explanation of complex topics, and Python coding to execute data pipelines, train ML/DL models, and deploy them on container-based orchestrators . What we need to see : - Excellent verbal, written communication, and technical presentation skills in Japanese. Business level English communication is also a requirement. - BS or MS in Computer Science, Engineering , Mathematics , or Physics (or equivalent experience) - 5+ years of industry or academic experience related to Generative AI or Deep Learning - Strong coding development and debugging skills. Including experience with Python, C/C++, Bash, and Linux - Demonstrated experience with cluster orchestration tools including Docker, Kubernetes, or SLURM across cloud service providers and on premises - Ability to multitask effectively in a dynamic environment - Strong analytical and problem-solving skills - Clear written and oral communication skills with the ability to effectively collaborate with management and engineering - Have a strong desire to share knowledge with clients, partners and co-workers Ways to stand out from the crowd: - Expertise in deploying large-scale training and inferencing pipeline - Experience with pre- training, post-training of transformer-based architectures for language or vision - A deep understanding of the latest generative AI or deep learning methods and algorithms - Experience using or operating Kubernetes, as well as experience writing or customizing Kubernetes configurations - Experience in designing agent-based systems: Experience working as an architect on the overall design, including optimal infrastructure, agent architecture, and authentication systems NVIDIA is widely considered to be one of the technological world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative and autonomous, 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 HPC and AI Operation Engineer
NVIDIA is looking for a Senior HPC & AI Operation 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 system administrator 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 will be doing: - Deploy, manage and maintain large scale HPC/AI clusters - Managing Linux job/workload schedules and orchestration tools - Support and maintain continuous integration and delivery pipelines - Troubleshooting and fixing, bottom up from bare metal, operating system, software stack and application level - Supporting Research & Development activities and engaging in POCs/POVs for future improvements What we need to see: - Bachelor's Degree in Computer Science, Engineering, or a related field; or equivalent experience - 5+ years of experience - Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software - Experience with job scheduling workloads and orchestration tools such as Slurm, K8s - 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. - 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, automation and configuration management tools such as Jenkins, Ansible, Gitops - Knowledge of Networking Protocols like InfiniBand, Ethernet - Experience with virtual systems (for example VMware, Hyper-V, KVM) - Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud) 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 has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. We have 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. 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 IL-Hybrid
Manager, Customer Solution Architect and Applicati...
NVIDIA's groundbreaking invention of the GPU in 1999 not only sparked the growth of the PC gaming market but also redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning has ignited the modern AI era, positioning the GPU as the brain behind computers, robots, and self-driving cars that can perceive and understand the world around them. NVIDIA is seeking a Customer Solution Architecture and Application Engineering Manager to join our team. In this pivotal role, you will collaborate with our key hardware design teams to enable NVIDIA's next-generation Embedded products and system solutions. Your responsibilities will include leading a Partner Enablement team to ensure product quality and reliability, optimize system performance, and enhance the integration process. You will engage with customers from New Product Introduction (NPI), design integration, and validation stages, all the way through to mass production deployment. This is a unique opportunity to lead Embedded solutions into the fastest-growing markets, including artificial intelligence, deep learning, and advanced computing! We have a rare chance to change the world with our next-generation solutions at the forefront of advanced technology, making a significant impact on our daily lives. If you are passionate about technology that drives growth in AI markets and want to be part of a diverse team that is making a difference, we encourage you to apply now to join NVIDIA! What You’ll Be Doing: - Lead a team to collaborate with major Tier-1 and key OEM customers, as well as internal teams, to develop future Embedded architectures and roadmaps. - Lead a team working alongside hardware design, firmware, software, sensors validation and AI algorithm teams to integrate NVIDIA's Embedded solutions into our customers’ products. - Define system-level requirements and specifications for Embedded architectures using NVIDIA SoC solutions, while maintaining design documentation, test plans, and other customer enablement materials. - Evaluate and enhance system performance, power efficiency, and thermomechanical integration, while simultaneously providing internal teams with laser-focused feedback for future improvements. - Lead a team to address complex technical design issues at all levels. - Collaborate with multi-functional teams at NVIDIA to ensure customer solutions are extraordinarily optimized to be the highest-performing solutions in the world. What We Need to See: - Expertise in thermal, mechanical, and electrical (TME) engineering, with experience ranging from nano-electronic and micro-mechanical board design to the integration of large-scale Automotive and Robotic systems. - 10+ overall years of proven experience and 3+ years in a management role. - BS or equivalent degree in EE/CE/CS engineering field or equivalent experience - Consistent track record of leading a team and working with multidisciplinary groups (hardware, firmware, software, validation, project management, sensors, and AI algorithm developers). - In-depth knowledge of AI hardware products and applications. - Exceptional communication skills, both external and internal, coupled with strong collaboration abilities. - A deep passion for complex problem-solving on a technical and process level, while comprehending the broader implications and trade-offs involved. NVIDIA offers highly competitive salaries and a comprehensive benefits package. Our team comprises some of the most experienced and dedicated individuals in the world, and due to outstanding growth, our extraordinary engineering teams are growing rapidly. If you are a creative and autonomous engineer with a genuine 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 196,000 USD - 310,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 11, 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 Systems Engineer, Datacenters
As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing datacenter deployments as well as establishing a data-driven approach to hardware design and system software development. The role of a Deep Learning Systems Engineer would be to analyze the performance and power consumption of deep learning applications on datacenter-class hardware and significantly influence the design and optimization of datacenters. Do you want to influence the development of high-performance Datacenters designed for the future of AI? Do you have an interest in system architecture and performance? In this role you will find how CPU, GPU, networking, and IO relate to deep learning (DL) architectures for Natural Language Processing, Computer Vision, Autonomous Driving and other technologies. Come join our team, and bring your interests to help us optimize our next generation systems and Deep Learning Software Stack. What you'll be doing: - Help develop software infrastructure to characterize and analyze a broad range Deep Learning applications - Evolve cost-efficient datacenter architectures tailored to meet the needs of Large Language Models (LLMs). - Work with experts to help develop analysis and profiling tools in Python, bash and C++ to measure key performance metrics of DL workloads running on Nvidia systems. - Analyze system and software characteristics of DL applications. - Develop analysis tools and methodologies to measure key performance metrics and to estimate potential for efficiency improvement. What we need to see: - A Bachelor’s degree in Electrical Engineering or Computer Science or equivalent experience (Masters or PhD degree preferred). - 8 years or more of relevant experience. - Experience in at least one of the following: - System Software: Operating Systems (Linux), Compilers, GPU kernels (CUDA), DL Frameworks (PyTorch, TensorFlow). - Silicon Architecture and Performance Modeling/Analysis: CPU, GPU, Memory or Network Architecture - Experience programming in C/C++ and Python. Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm) is a plus. - A deep understanding of computer system architecture and performance analysis is essential for success in this role. Applicants should have demonstrated hands-on experience in these domains. - Demonstrated ability to work in virtual environments, and a strong drive to own tasks from beginning to end. Prior experience with such environments will make you stand out. Ways to stand out from the crowd: - Background with system software, Operating system intrinsics, GPU kernels (CUDA), or DL Frameworks (PyTorch, TensorFlow). - Experience with silicon performance monitoring or profiling tools (e.g. perf, gprof, nvidia-smi, dcgm). - In depth performance modeling experience in any one of CPU, GPU, Memory or Network Architecture - Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm). - Prior experience with multi-site teams or multi-functional teams. 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're 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 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 11, 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 System Simulation Architect
Do you want to help drive the development of CPU architectures to fuel the explosive growth in artificial intelligence (AI) / deep learning (DL), high-performance computing (HPC), gaming, virtual reality, and autonomous vehicles? Come join the CPU performance architecture team as a Senior System Simulation Architect and help us push performance boundaries for NVIDIA’s line of CPU products! What you’ll be doing: Develop full-system functional models capable of running complex multi-threaded heterogeneous (CPU/GPU) workloads – with special focus on the CPU subsystem. Integrate functional models from various frameworks with RTL simulators and emulators, hardware (HW-in-the-loop), and detailed performance models. Bring up system and application software in simulation and emulation – including firmware, Linux, drivers, benchmarks, and CPU/GPU workloads such as deep-learning (DL) and high-performance computing (HPC) workloads. Port/extend/develop system software (firmware, OS, and drivers) to meet workload simulation needs. Support CPU architects and performance engineers in their use of functional models, performance models, and emulation to drive next-generation CPU architectures. What we need to see: BS/MS in EE, CE, or CS or equivalent experience 6 or more years of relevant experience Excellent C/C++/Python programming skills Experience in development of functional simulators and/or low-level software (OS, firmware, drivers); preferably both Excellent debugging skills – of both system software/firmware and application software Experience with the ARM ISA Excellent communication and teamwork skills Ways to stand out from the crowd: Experience working with hardware emulators and/or FPGAs Background in CPU workload analysis (SimPoint, etc.) Experience with Linux kernel bringup and debug Familiarity with CUDA Experience with CPU/GPU application development and optimization in Pytorch, TensorFlow, and similar frameworks 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. #ArchitectYourFuture 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: 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 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.
Senior Accelerated Computing Architect
We are now looking for a Senior Accelerated Computing Architect! NVIDIA is developing software and system architectures for accelerated high performance computing, scientific computing, machine learning, AI, datacenter, and automotive computing. This position offers you the opportunity to make a meaningful impact in a fast-moving, technology focused company. What you'll be doing: - Performing in-depth analysis and optimization to ensure the best possible performance on current and/or next-generation NVIDIA GPUs. - Creating and optimizing core parallel algorithms, data structures, and reference codes to provide the best possible solutions for NVIDIA GPUs. - Understanding and analyzing the interplay of hardware and software architectures on core algorithms, programming models, and applications. - Actively collaborating with the hardware design, software engineering, product, and research teams to guide the direction of accelerated computing. - Diving into accelerated computing applications to facilitate software-hardware co-design. - Writing up and presenting your work by writing white papers, conference publications, official blog posts, patent applications, etc. as appropriate. What we need to see: - An MS or Ph.D. in Computer Science, Computer Engineering or Electrical Engineering, or equivalent experience - 6+ years of relevant work experience - Strong mathematical fundamentals, including linear algebra and numerical methods. - A passion for performance optimization. - Hands-on experience with the massively parallel GPU programming model, e.g. CUDA or OpenCL. Familiarity with APIs for multi-node communication, like MPI or OpenSHMEM/NVSHMEM, is a plus. - Strong knowledge of C and C++ with solid understanding of software design, programming techniques, and algorithms. Familiarity with threading APIs for multicore CPUs and Unix-style Inter-process Communication (IPC) APIs is a plus. - Familiarity with Python is a plus. - Good communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills. - Experience benchmarking, profiling characterizing workloads on GPU and CPU clusters. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people in the world working for us. Are you creative and autonomous? Do you love the challenge of pushing an architecture to its limits? If so, 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 11, 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.
Solutions Architect, OEM AI Factory Infrastructure
In this role, you will be a contributing member of the OEM AI Factory SA team. Our work encompasses MEP (Mechanical Electrical Plumbing), Ethernet and Infiniband networking, DevOps, HPC/AI workloads, Cluster Administration and Site Reliability Engineering. You will acquire insight into various facets of AI Factories deployments. Applicants should be familiar with Linux system administration, Python, and networking concepts. Solid understanding of Slurm and data sciences is a plus. Our Team is responsible for OEM AI factory build engagements - which means that we work with our OEM partners (Dell, HPE, Lenovo and others) to use NVIDIA solutions integrated in their platforms. NVIDIA certified servers include GB200/300 NVL72, along with our software stack that assists with the deployment, configuring, validating and monitoring for the AI Factories of the future. What you’ll be doing: - Collaborating with solution architects, engineering or product teams! - Understanding technical needs of partners and customers - Developing proof of concept projects with NVIDIA technologies. - Assisting with key takeaways, documenting and sharing. - Educating our Partners through hands-on trainings. What we need to see: - BS, MS, or PhD in Computer Science, Computer Architecture, Electrical Engineering, Math, Physics, Data Science, or related technical fields (or equivalent experience) - 5+ years experience - Strong skills in one or more programming languages (Python, C, C++, etc.) - Excellent presentation, communication and collaboration skills - Ability to work independently and with a cross-functional team - Comfortable multi-tasking in a fast-paced environment with changing requirements - Strong analytical and problem-solving skills Ways to stand out from the crowd: - Experience with NVIDIA GPUs and software libraries - Work experience within an engineering or research community - A computer architecture, software engineering, or data science foundation - Academic or industry familiarity with GPUs, AI, CUDA, or related technologies - Ability and eagerness to dig into unfamiliar territories to take on problems relying on experience from previous work with data center infrastructure experience, from hardware up through technology stack NVIDIA is renowned as one of the most coveted employers in the tech world. We’re home to some of the industry's brightest and most innovative minds. If you’re excited about witnessing how a global technology leader stays at the cutting edge, 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 11, 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 Relations Manager, Higher Education and...
We are seeking a dynamic, mission-driven Developer Relations Manager to engage leading research labs. In this role, you will work directly with research labs to accelerate the adoption of NVIDIA’s sophisticated AI and computing platforms. The ideal candidate combines deep, technical expertise with strong experience in research engagement and a proven track record of turning advanced technologies into meaningful, research-focused results. What you'll be doing: Act as a trusted technical advisor for research labs, identifying and accelerating high-impact workloads by integrating NVIDIA's frameworks, libraries, and core software stack into research projects. Map and continuously assess the research ecosystem to identify institutional growth opportunities and inform long-term technology strategies Stay current on research papers across affiliated domains to anticipate emerging trends and provide technical direction on future collaboration areas. Collaborate cross-functionally with Research Account Managers, Solution Architects, and Business Development teams to drive researcher enablement Forge closer ties with lab personnel, understanding organizational dynamics and the full scope of research being conducted. Attend domain scientific conferences and facilitate NVIDIA participation alongside other subject matter experts. Represent the needs of researchers internally by translating academic feedback into actionable insights that shape product development, education programs, and platform roadmaps. What we need to see: PhD in Computer Science, AI, Machine Learning, Computational Science, Physics, or a related technical field; or equivalent experience demonstrating comparable research depth. 3+ years of experience. Deep expertise applying AI to computational physics, particle physics, astrophysics, plasma/fusion, quantum systems, materials science, climate/earth systems, or scientific simulation. Strong fluency in AI methods relevant to physics, including neural operators, surrogate models, physics-informed ML, differentiable simulation, simulation-based inference, generative modeling, and uncertainty quantification. Understanding of physics research workflows, including HPC simulations, numerical solvers, experimental/sensor data, large-scale instruments, inverse problems, and GPU-accelerated scientific pipelines. Ability to engage top physics and national lab researchers on physical consistency, interpretability, numerical accuracy, reproducibility, simulation speedups, and scientific validity. Research credibility through publications, open-source scientific software, academic or national lab collaborations, technical leadership, or hands-on work in AI for physics or computational science. Ways to stand out from the crowd: Experience with NVIDIA technologies and platforms such as CUDA, CUDA-X libraries, NVIDIA AI Enterprise, NIM, NeMo/Nemotron, PhysicsNeMo, cuQuantum, Omniverse, Isaac, RAPIDS, TensorRT, Triton Inference Server, or DGX/accelerated computing systems. Established relationships with leading academic labs, research institutes, national labs, or major open source research communities. Track record translating frontier research into demos, reference architectures, workshops, technical content, or developer enablement programs. Experience presenting at academic conferences, research workshops, technical summits, or university facing events. Ability to identify emerging research trends and convert them into strategic opportunities for collaboration, platform adoption, and ecosystem growth. 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 other objective job-related factors. The expected base salary ranges for this position are: 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 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.
Senior AI Engineer, Agents and Developer Workflows
Today, NVIDIA is 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, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. NVIDIA is hiring senior software engineers in its Infrastructure, Planning and Process Team (IPP), to accelerate AI adoption across various engineering workflows within the company. IPP is a global organization within NVIDIA. The group works with various other teams within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure and software development workflow needs. As a senior engineer on AI Workflow, you will create and establish tools and software solutions that leverage Large Language Models and agentic AI to automate end to end software engineering workflows and enhance the productivity of engineers across NVIDIA. What you’ll be doing: - Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability - Experience designing, developing, and deploying AI agents to automate software development workflows and processes. - Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR). - Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures. - Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge. What we need to see: - BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience. - Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent development - Strong background in implementing AI solutions to solve real-world software engineering problems. - Hands-on experience on Python/Java/Go with extensive python scripting experience. - Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch. - Full-stack, end-to-end development expertise, with proficiency in building and integrating solutions from the front-end (e.g., React, Angular) to the back-end (Python, Go, Java) and managing data infrastructure (SQL/NoSQL). - Experience with tools for CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools. - Good understanding of distributed systems, understanding of microservice architecture and REST APIs. - Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams. Ways to stand out from the crowd: - Proven expertise in applied AI, particularly using Retrieval-Augmented Generation (RAG) and fine-tuning LLMs on enterprise data to solve complex software engineering challenges. - Experience delivering large-scale, service-oriented software projects under real-time constraints, demonstrating an understanding of the complex development environments this role will optimize. - Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data. We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. We are building a team that will truly change the world. If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, we would love for you to join us.
Senior Solutions Architect, GPU Performance and LL...
Join our team at NVIDIA and help bring AI solutions to our largest customers. We are seeking an expert Solutions Architect to assist customers in building AI/ML and HPC software solutions at scale. As a member of our Solutions Architecture team, you will collaborate with strategic customers, providing end-to-end technology solutions and technical support based on our product strategy. Come join us! What you’ll be doing: - Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies. - Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions. - Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference. - Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions. - Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers. - Analyzing and developing solutions for customer performance issues for both AI and systems performance. What we need to see: - BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience. - 8+ years of engineering (performance/system/solution) experience. - Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference. - Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application. - Effective engineering program management with the capability of balancing multiple tasks. - Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments. Ways to stand out from the crowd: - Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.). - Familiarity with deep learning architectures and the latest LLM developments. - Background with NVIDIA hardware and software, performance tuning, and error diagnostics. - Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking. - Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency. 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 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.
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