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Senior Software Developer, AI Networking
NVIDIA is changing the world of AI Networking with groundbreaking technology. We are excited to be adding an AI Networking Software Developer to our AI Networking SW development and codesign team. We are working with the latest NVIDIA hardware and technologies. We do full stack benchmarking for Data Center scale systems for AI training/inference and lower level benchmarks. We strive for automation and develop many tools in-house yet adopt community accepted practices and frameworks. Moreover we give back to community developing our own tools in public GitHub repositories. Our goal is to ensure that large-scale systems deliver expected performance in practice, not just on paper, by uncovering bottlenecks and driving continuous improvements. What you'll be doing : - Developing AI networking communication frameworks and applications running in production on the world’s largest supercomputers and data centers. - Develop production tools and benchmarks used by multiple teams inside and outside NVIDIA. - Enable new AI models within our benchmarking infrastructure and deliver insights through end-to-end analysis of large-scale workloads across hardware and software stacks. - Design and implement automation systems, including large-scale parameter search to identify optimal configurations across complex systems. - Collaborate closely with networking and hardware teams to co-design new features and software interfaces in a fast-paced, evolving environment. What we need to see: - B.Sc., M.Sc degree in Computer Science / Software engineering or equivalent experience. - 5+ years of experience. - Professional Python development experience. We seek individuals who build maintainable, long-lived tools that do not impose a heavy burden on the team in terms of maintenance. - Solid Linux expertise and passion for working extensively in command-line environments. - Ability to work across a broad and evolving stack, with a strong drive to learn—from hardware and networking up to large-scale AI systems running across entire clusters Ways to stand out from the crowd: - Knowledge and/or experience with modern AI ecosystem: PyTorch, LLMs, inference and training. - Familiarity with cluster orchestration systems such as Slurm or Kubernetes. - Knowledge in MPI and HPC, InfiniBand, Ethernet and Networking. - Experience in performance optimizations For two decades, we have pioneered visual computing, and the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning. This new model - where deep neural networks are trained to recognize patterns from massive amounts of data - has shown to be deeply effective at solving some of the most complex problems in everyday life. NVIDIA is widely considered to be one of the technology world's most desirable companies to work for. Are you creative and driven? Do you love a challenge? 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 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 July 19, 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 Machine Learning Engineer - Automotive
Intelligent machines powered by Artificial Intelligence computers that can learn, reason, and interact with people are no longer science fiction. Today, a self-driving vehicle powered by AI can meander through a country road at night and find its way. NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots, and self-driving vehicles that can perceive and understand the world. Our team is building the machine learning backbone of the Perception component for NVIDIA DRIVE AV. We are seeking the best Machine Learning Engineers with a background in computer vision, LiDAR & camera perception, and AI infrastructure who are passionate about solving the hardest problems for self-driving cars. Are you interested in inventing human-level AI for perception under real world conditions? If so, join us! What You'll Be Doing: - Model Development: Design, train, and optimize innovative machine learning models for LiDAR/camera perception (e.g., object detection/classification, semantic segmentation, tracking). - Develop and coordinate entire ML workflows, covering data pipelines, model training, model metrics, continuous performance instrumentation, and reporting. - Productization: Take ML models and algorithms from initial evaluation and experimentation all the way to product level on the NVIDIA DRIVE AV platform, developing highly efficient product code in C++. - Innovation: Keep track of the latest developments in machine learning, and incorporate techniques that improve platform performance. - Collaborate with LiDAR/camera teams, developers, engineers, and managers to turn complex ideas into reliable solutions for autonomous driving. What We Need to See: - MS in Computer Science, Engineering, or a related field, or equivalent experience. - 6+ years of relevant proven industry experience applying machine learning to address real-world problems. - Strong C++ and Python programming and debugging skills with experience in developing for large, complex systems. - Deep practical experience applying machine learning to lidar/camera perception in automotive or related fields. - Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and a strong understanding of the mathematical foundations of ML. - Building and sustaining training and essential metric workflows for large-scale datasets. - Excellent communication and analytical skills. Self-motivated drive to solve hard problems. Ways to Stand Out From the Crowd: - LiDAR or Camera Perception Experience: Proven track record of developing and shipping deep learning models for LiDAR/Camera in a production environment. - Advanced Model Knowledge: Familiarity with modern network architectures like Transformers and their application to visual recognition tasks. - AV Production Experience: A history of delivering ML features and models into a production autonomous vehicle stack or a related robotics product. - Performance Optimization: Experience with model optimization for real-time inference on embedded or automotive platforms (e.g., using TensorRT). We believe that realizing self-driving vehicles will be a defining contribution of our generation (e.g., traffic accidents are responsible for ~1.25 million deaths per year worldwide). We have the funding and scale, but we need your help on our team. NVIDIA is widely considered to be one of the technology world’s most desirable employers with some of the most brilliant and talented people in the world working here. If you're creative and autonomous, we want to hear from you!
Senior Radar Perception Engineer, Obstacle Foundat...
Intelligent machines powered by artificial intelligence—computers that can learn, reason, and interact with people—are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence, acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We are seeking an exceptional Senior Radar Perception Engineer to help design and productize NVIDIA’s next-generation autonomous driving perception stack. You will work on the core 3D radar and multi-modal obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, radar-centric foundation models, and multi-sensor fusion techniques where they add real value. What you’ll be doing: - Architecture & Roadmap: Develop and improve the technical design, architecture, and roadmap for radar-based 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art DNN and transformer-based architectures. - Radar Perception Innovation: Conduct applied research on deep learning models to maximize the information content of radar point cloud data at every representation level. Tackle radar perception’s hardest problems: low and non-uniform angular resolution, multipath and ghost targets, micro-doppler signatures for small targets, and severe class imbalance. Explore weakly-supervised pretraining and improve radar perception via large auto-labeled datasets. - Model Design & Fusion: Design and implement advanced 3D perception models utilizing radar inputs (ranging from low-level range-doppler/azimuth-elevation maps to sparse/dense point clouds) and multi-sensor fusion (camera, radar, lidar) for obstacle detection, tracking, and Bird’s-Eye-View (BEV) scene understanding. - Sensor & Stack Integration : Drive radar sensor evaluation, selection, and layout optimization to support L2-L4 autonomous driving applications, ensuring seamless multi-sensor fusion. - Production Deep Learning: Build efficient, production-grade deep learning models: define objectives with the team, select and prototype architectures, run experiments, and follow best practices for training and evaluation, using techniques such as large-scale radar pretraining, cross-modal distillation (e.g., lidar-to-radar), and parameter-efficient fine-tuning (e.g., LoRA). - KPIs & Error Analysis: Help define and maintain KPI frameworks to quantify radar perception performance; analyze large-scale real and synthetic datasets to identify failure modes unique to radar (e.g., multipath reflections, clutter, ghost objects) and systematically improve accuracy, robustness, and efficiency. - Data Strategy & Auto-Labeling: Contribute to the data strategy for radar perception: specify data and labeling requirements, help prioritize data collection and annotation, and collaborate with data and ground-truth teams, incorporating model-assisted workflows (e.g., active learning, automated radar labeling via lidar/camera foundation models) and model-in-the-loop tooling. - Cross-Functional Productization: Collaborate with safety, systems, and software teams to ensure radar perception solutions meet product requirements for safety, low latency, resource usage, and software robustness, and are ready for deployment at scale. What we need to see: - Industry Experience: 12+ years of hands-on experience developing deep learning–based perception, radar signal processing, or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production. - Data-Driven Workflows: Proven experience in data-driven development, including close collaboration with data, labeling, and ground-truth teams on radar data strategy, labeling quality, and iterative model improvement. - Software Engineering: Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software. - Collaboration: Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams spanning AI, hardware, and safety engineering. - Education: BS/MS/PhD in Computer Science, Electrical Engineering, Robotics, or related fields (or equivalent experience). Ways to stand out from the crowd: - Radar & Multi-Modal Scale: Experience designing and deploying radar-based or multi-modal perception solutions for autonomous driving or robotics using deep learning at scale. - Embedded Optimization: Hands-on experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms, including optimization for latency, memory, and compute constraints, and familiarity with modern architectures (e.g., Transformers, BEV networks). - Signal Processing Depth: Deep understanding of radar physics and digital signal processing fundamentals (FMCW, beamforming, CFAR, micro-Doppler) and how to cleanly interface traditional signal processing outputs with downstream deep learning models. - Academic/Research Track Record: Strong publication record or recognized contributions in deep learning, radar perception, multi-sensor fusion, or autonomous systems at leading conferences/journals (e.g., CVPR, ICCV, NeurIPS, IROS). - GPU Acceleration: Experience with CUDA development and optimizing training or inference pipelines through custom CUDA kernels or other GPU-accelerated components to handle high-bandwidth raw radar or tensor data. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 19, 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 Data Engineer, PE
We are looking for a Senior Data Engineer to join the manufacturing data Engineering team and help us craft data collection solutions, quality control methodologies and monitors, support data enlargement scale. As a Data Engineer, you will play a significant role in bridging the gap between machine learning and software engineering. Your primary responsibility will be to develop, deploy, and maintain the infrastructure, data pipelines and workflows required for the end-to-end solution collecting the data till loading to data warehouse. If you are genuinely passionate about data engineering platforms, methodologies and possesses excellent problem-solving, we'd love to hear from you! What you’ll be doing: - Collaborate with multi-functional teams, including full stack engineers, data scientists, data engineers, and DevOps, to craft, implement robust reliable data pipelines, infrastructure and workflows. - develop and support data models, schemas, and database structures that provide blazing-fast analytics performance. Constantly optimize data workflows to ensure flawless real-time and batch data processing. - Implement data quality checks and monitoring mechanisms to ensure data integrity and accuracy at every stage. detect and resolve bottlenecks swiftly to maintain a highly available and reliable data ecosystem. - Control, monitor and optimize worldwide production servers. - Build and maintain scalable data pipelines, ensuring efficient data storage, retrieval, and transformation. - Stay ahead of the curve in data engineering technologies and trends. Introduce new tools, techniques, and standard methodologies to improve our data infrastructure, empowering data scientists and analysts alike. - Feed a culture of learning and knowledge-sharing within the team. Guide and mentor junior data engineers, applying your expertise to uplift the entire department. What we need to see: - Bachelor’s or master’s degree in computer science, Engineering, or a related field. - 5+ years of relevant experience. - Demonstrated track record as a hands-on Data Engineer, driving the successful delivery of sophisticated data projects. Your experience speaks volumes. - Experience with cloud-based data platforms like AWS, Azure, or GCP. You harness the power of the cloud to unlock data's full potential. - Strong programming skills in languages such as Python or Scala, with experience in building scalable and efficient systems. - Experience with containerization technologies like Docker and orchestration tools like Kubernetes. - Solid knowledge in Linux environment. Ways to stand out from the crowd: - Attention to detail is unwavering. You take pride in delivering data of the highest quality, turning it into insights that power critical business decisions. - Experience working and data engineering frameworks such as Kafka, Cloudera, Spark, Airflow or Hadoop. - Growing in a multifaceted environment, able to balance multiple priorities admirably without compromising on quality or precision. 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. 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 Architect
We are now looking for a Senior Deep Learning Systems Architect! NVIDIA is seeking architects like you to help design hardware accelerator and processor architectures that enable state of the art machine learning and data analytics algorithms and applications on our next-generation mobile, embedded and datacenter platforms. This position offers you the opportunity to have a real impact in a dynamic, technology-focused company. What you'll be doing: - As a member of our deep learning architecture team, you will contribute to features that help next-generation GPUs and systems advancing the state of AI. - This position requires you to keep up with the latest DL research and collaborate with diverse teams (internal and external to NVIDIA), including DL researchers, hardware architects, and software engineers. - As a system architect for NVIDIA’s offerings for AI systems, you will participate in engineering projects and co-design architecture for systems from conception, specification and prototyping. - Understanding various AI/DL workloads and their mapping to underlying HW and Systems. Identifying potential improvements and bottlenecks, proposing solutions to address existing gaps, and accelerate/improve current systems/methods. - Comprehensive analyses from first principles of various deep learning techniques, system optimizations to build out analytical models as well as implementing prototypes, and benchmarking to test/prove ideas. What we need to see: - MS (or equivalent experience) or PhD degree in computer science, computer architecture, electrical engineering or related field with 10+ years of relevant work experience. Additional equivalent experience in several of the relevant areas listed below can substitute for an advanced degree. - Strong background in at least a few of the following relevant areas is required in your work history: Machine learning (with focus on Deep Neural Networks), including a solid understanding of DL fundamentals; Experience adapting and training DNNs for various tasks; Experience developing code for one or more of the DNN training frameworks (such as PyTorch, TensorFlow or JAX): Numerical analysis, Performance analysis and optimization & Computer architecture. - Programming fluency with C++ and ideally Python. - Work experience with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP) is a huge plus. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun. 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, autonomous and love a challenge, we want to hear from you! Come, join our Deep Learning Architecture team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 19, 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 Solutions Architect, Agentic AI
We are looking for a Senior Solutions Architect to help leading Enterprise ISVs design, build, optimize, and deploy production-grade Agentic AI systems on NVIDIA’s accelerated computing platform. In this role, you will partner with strategic software companies to translate frontier AI capabilities into reliable enterprise products, spanning multi-agent orchestration, RAG, tool use, model customization, and production deployment. We work at the intersection of partner engineering, NVIDIA’s AI platform, and product development. You will lead sophisticated technical projects from initial exploration through architecture, prototyping, performance optimization, production rollout, and field enablement. Together, we will help partners adopt NVIDIA technologies and GPU-accelerated infrastructure to bring next-generation AI products to market. What you'll be doing: - Lead technical delivery for strategic Agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale. - Design and build enterprise-grade agentic systems, including multi-agent workflows, tool-using agents, RAG-integrated applications, planning, memory, evaluation, and guardrail patterns. - Lead deep architecture reviews with partner engineering teams, driving tradeoffs across model quality, latency, efficiency, cost, retrieval quality, reliability, safety, security, and observability. - Build hands-on PoCs, benchmarks, reference architectures, and reusable blueprints that help Enterprise ISVs and NVIDIA field teams move from exploration to production. - Guide partners on model customization and post-training workflows, including supervised fine-tuning, reinforcement learning methods, human or AI feedback, direct preference optimization, PEFT/LoRA, synthetic data generation, evaluation, and regression analysis. - Work with agent harnesses and execution environments such as OpenShell, OpenAI Agents SDK, LangGraph, LlamaIndex, LangChain, CrewAI, Semantic Kernel, or similar frameworks. - Translate partner deployment findings into actionable feedback for NVIDIA Product and Engineering, so we can improve our platforms, tools, and field guidance. What we need to see: - BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience. - 8+ years of engineering, solutions architecture, applied ML, or technical deployment experience. - Consistent track record leading complex AI, ML, distributed systems, or enterprise software deployments from prototype to production. - Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments. - Strong programming and debugging skills in Python and Linux environments, with experience in PyTorch, TensorFlow, or similar deep learning frameworks. - Deep understanding of agentic AI architectures, including tool use, orchestration, memory, retrieval, planning, evaluation, guardrails, and failure handling. - Experience with model customization or post-training techniques such as SFT, RL/RLHF/RLAIF, DPO or relevant equivalent experience, reward modeling, LoRA/PEFT, quantization-aware optimization, or model evaluation. - Ability to lead ambiguous partner engagements, influence senior engineering collaborators, and communicate clearly with technical and executive audiences. Ways to stand out from the crowd: - Hands-on experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Triton, TensorRT-LLM, or NIM Operator. - Experience building post-training pipelines for reasoning, tool use, domain adaptation, enterprise task performance, or agent behavior improvement. - Experience with agent harnesses, sandboxed execution, policy enforcement, OpenShell-like environments, or secure enterprise agent runtime build. - Recognized expertise in RAG, model customization, agent orchestration, enterprise AI security, or GPU-accelerated AI infrastructure, with field-facing technical presence through workshops, architecture reviews, talks, whitepapers, or developer enablement. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 20, 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.
Solutions Architect, Physical AI and Omniverse
NVIDIA is a leader in accelerated computing, artificial intelligence, and next-generation platform innovation. Our Worldwide Field Operations Solutions Architecture team supports third-party software vendors, partners, and customers. We transform advanced technologies into practical, repeatable solutions. We are hiring a Solutions Architect to boost adoption of NVIDIA DSX Sim, Omniverse libraries, and AI agent skills. This position will establish DSX Sim as a shared, simulation-ready decision layer for AI factory creation! We also provide partners with actionable methods to embed accelerated rendering, physics, storage, streaming, and user interface capabilities into their applications. This role connects customer demands with field delivery and product engineering, improving how AI factories and industrial digital twins are developed, validated, and put into operation. What you will be doing: - Assist independent software vendors, ecosystem partners, and lighthouse customers in assessing and adopting technologies within DSX Sim, and Omniverse libraries. - Architect and demonstrate simulation workflows that help customers build, validate, optimize, and operationalize AI factory digital twins. - Collaborate with partners to build and validate simulation-ready asset pipelines using OpenUSD, SimReady specifications, engineering data, multi-physics simulation, and operational inputs. - Drive incorporation of Omniverse libraries (ovRTX, ovPhysx, ovStorage, usd-agents, etc) into partner applications, services, and enterprise workflows. - Develop reusable reference architectures, demonstrations, sample workflows, benchmarks, and proof-of-concept evaluations that address customer challenges. - Translate technical and business requirements into clear solution plans while coordinating with sales, product engineering, developer relations, and partner teams to resolve blockers and advance adoption. - Gather field insights, advocate for partner needs, and contribute technical mentorship that improves product direction, enablement resources, and team execution. What we need to see: - Bachelor’s degree in computer science, engineering, or a related technical field, or equivalent experience. - 2+ years of relevant engineering, technical sales, or solution architecture experience; candidates considered for the higher level typically bring 5+ years of related experience. - A solid base in one or more relevant areas, such as computer graphics, physically based rendering, physics simulation, engineering simulation, digital twins, or accelerated computing. - Practical understanding of three-dimensional workflows and asset pipelines through OpenUSD or similar scene-description, modeling, and data-interchange technologies. - Experience programming in Python and a higher-level language such as C, C++, or Java. - Hands-on success developing technical prototypes, setting up evaluations, benchmarking solutions, or supporting customer implementations of external libraries. - Ability to manage technical relationships, explain sophisticated concepts clearly, and work closely with developers at external software companies, NVIDIA partners, and internal collaborators. Ways to stand out from the crowd: - OpenUSD certification or substantial hands-on work with OpenUSD composition, schemas, validation, optimization, or asset-pipeline development. - Background crafting digital twins or simulation workflows for AI factories, data centers, architecture and engineering, industrial systems, or other complex physical environments. - Knowledge of high-performance rendering techniques, physics, and simulation technologies such as NVIDIA RTX, PhysX, CUDA, multi-physics solvers, or AI surrogate models. - Success enabling partner solutions or building workflows such as computer-aided-design conversion, synthetic data generation, defect detection, neural reconstruction, or simulation-ready asset creation. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 20, 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 Solutions Architect, AI Infrastructure Ente...
NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI and accelerated computing technologies. At NVIDIA, our solutions architects work across product, engineering, sales, developer relations, business development, and partner teams to help customers design, deploy and optimize AI infrastructure. This role will focus on helping ISVs adopt NVIDIA accelerated infrastructure for training, fine-tuning, inference, retrieval, and agentic AI workloads. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA! You will serve as a technical advisor for accelerated systems architecture, GPU and networking systems, cluster design, architectures, orchestration, validation, and production deployment for AI data centers. What You Will Be Doing: - Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance - Advise on the design, build-out, and optimization of accelerated AI infrastructure, including large-scale clusters - Support infrastructure design across compute, networking, storage, containers, observability, security, power, and data center operations - Drive adoption of systems monitoring, telemetry, and management tools to improve cluster utilization, reliability, performance and workload insight - Build repeatable reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos and whitepapers - Travel up to 20% customer meetings may be required What We Need To See: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) - 8+ years of hands-on experience in AI infrastructure, accelerated computing, distributed systems, cloud infrastructure, high-performance computing, or machine learning platforms - Strong experience designing, deploying, and operating accelerated computing infrastructure at scale - In-depth knowledge of AI cluster orchestration, scheduling, automation and CI/CD deployment pipelines - Understanding of data center networking technologies such as InfiniBand, Ethernet, RDMA, network configuration or performance tuning - Familiarity with infrastructure requirements for AI workloads, including distributed training, inference serving, model deployment, storage performance, and cluster reliability - Excellent presentation, communication, problem-solving, documentation, and collaboration skills Ways To Stand Out From The Crowd: - Experience architecting AI factories, large GPU clusters, multi-node training environments, production inference platforms - Experience deploying LLM training, fine-tuning, RAG, and inference workflows on large-scale AI infrastructure - Experience evaluating cluster performance using benchmarks such as MLPerf, HPL, or workload-specific performance tests - Applications and systems-level knowledge of OpenMPI, NCCL, distributed training frameworks, and GPU communication patterns - Experience delivering technical training, workshops, whitepapers, blogs, or mentoring engineers, researchers, and customers on AI/HPC infrastructure 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 July 20, 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 Software Engineer, At Scale Compute Analysi...
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Join a team that analyzes large-scale datacenter workloads on GPU-accelerated clusters. You will turn telemetry and workload data into clear findings and visuals. You will partner with OS, container, GPU, and systems engineers. When useful, you will apply machine learning and deep learning techniques for categorization and forecasting. These will be coordinated into tools the team actually uses. What you’ll be doing: Analyze large-scale workloads and infrastructure signals to find application and platform improvement opportunities. Work with high-dimensional data: spot trends, tie changes to known events, summarize conclusions, and communicate results to engineers and leadership. Partner with the team to clarify questions, scope analyses, and document methods so others can extend your work. Build and maintain practical visualizations and lightweight implementations (e.g. ML/DL for classification/prediction) inside existing software workflows. What we need to see: 5+ years analyzing complex datasets, debugging data issues, and communicating trends clearly. BS or MS in Engineering, Mathematics, Physics, Computer Science, or equivalent experience. Strong Python and JavaScript; Comfortable being responsible for an analysis end-to-end. Hands-on use of telemetry / observability stacks (e.g. Grafana, Elasticsearch, Splunk). Shown grasp of core ML concepts; quick learner; strong analytical and problem-solving skills. Collaboration and communication. Ways to stand out from the crowd: TensorFlow or PyTorch Linux and HPC / large-scale or performance-sensitive environments Experience visualizing high-dimensional problems Diligent, action-biased analysis style 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 also offers a comprehensive benefits package. We provide health care coverage, dental and vision, 401(K), including company matching and after tax contributions, Employee Stock Purchase Program (ESPP), Employee Assistance Program (EAP), company paid holidays, paid sick leave, vacation leave, professional time off, life and disability protection. 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 Data Scientist, Cloud Gaming - Prescriptive...
Our team is building an innovative Data Platform that employs advanced analytics, including prescriptive modeling and constrained optimization, for real-time routing and scheduling at scale. This platform encompasses data collection, processing, visualization, analysis, anomaly detection, root cause identification, and predictive modeling. Our data include GPU availability/lifecycle, latency measurements from end users to data centers, game performance across different GPU types, and queuing information. Our active projects include applying optimization techniques to the cloud gaming experience; developing user behavior profiling, user base segmentation, actionable cluster detection, effective personalized recommendations, lifetime value analysis, and critical areas such as capacity management, prescriptive scheduling, and subscription churn analysis. We also focus on time-series forecasting, decision-making models, resource allocation, and latency minimization. You will wield the power of Data, AI, and Operations Research to help deliver a best-in-class cloud streaming performance and experience to our users across the world. Our technology stack relies on industry-standard components (Python, SQL, Delta Lake, Apache Spark, Databricks, MLflow, Grafana, Elasticsearch). What You will be Ding: - Build and deploy scalable ML/AI and optimization models to enhance demand forecasting, optimize capacity allocation, and develop user-specific feature engineering for real-time cloud gaming services. - Develop reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions for targeted business outcomes. - Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance, especially in the context of optimization outcomes. - Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques, informing prescriptive solutions. - Design and implement improvements to real-time prescriptive scheduling pipelines, using techniques like linear programming and constraint optimization, to enhance capacity utilization and user retention. - Improve productivity of the organization by mining petabytes of data for actionable insights for business and engineering, often through prescriptive recommendations. - Collaborate with a variety of partners to understand requirements, design robust solutions, and guide the team to deliver impactful results. - Leverage agentic AI to deliver best-in-class automation and programming solutions for complex analytical problems. What We Need to See: - BS/MS (or equivalent experience) with 6+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or related quantitative fields, with a strong emphasis on prescriptive analytics and optimization. - Strong background knowledge and practical experience in probability, statistics, AI/ML, prescriptive modeling, and optimization methodologies (e.g., linear programming, network flow, decision theory, and multi-armed bandit). - Strong coding skills, including the ability to write readable, testable, maintainable, and extensible code (primarily Python), with experience in libraries or tools relevant to optimization (e.g., Google OR-Tools). - Experience with common tools for data storage and processing, including drilling into problems of running large-scale software across large clusters - Strong experience in data cleaning, aggregation, transformation, and extraction, with an understanding of how data quality impacts performance. Ways to Stand Out from the Crowd - Good interpersonal and presentation skills in working with multiple partners, adept at explaining intricate analytical solutions and their business implications. - Experience in time series analysis and forecasting for demand prediction in optimization contexts is a plus. - Experience in active ML production pipelines (MLflow, Kubeflow) with a focus on deploying and monitoring optimization models is a plus. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. 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 July 20, 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
Deep Learning Performance Architect
NVIDIA is developing processor and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an expert deep learning system performance architect to join our AI performance modelling, analysis and optimization efforts. In this position, you will have a chance to work on DL performance modelling, analysis, and optimization on state-of-the-art hardware architectures for various LLM workloads. You will make your contributions to our dynamic technology focused company. What you'll be doing: - Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products - Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency. - Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations. - Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams. What we need to see: - BS, MS or PhD in relevant discipline (CS, EE, Math, etc.) or equivalent experience. - 3+ years work experience. - Experience with popular AI models (e.g., LLM and AIGC models) - Be familiar with typical deep learning SW framework (e.g., Torch/JAX/TensorFlow/TensorRT) - Knowledge and experience on hardware architectures for deep learning applications With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. deeplearning
Senior CUDA Test Development Software Engineer, SD...
NVIDIA is the world leader in GPU Computing. We are passionate about markets including Data centers, Gaming, Professional vision, Automotive, HPC and networking. We are well positioned as the “AI Computing Company”, and our GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, big data, modern data centers, smart cities, and driving autonomous vehicles. We have some of the most brilliant and talented people in the world working for us. If you are talented, bright, driven and if working with smart technical people across countries sounds interesting, this job is for you. We are the CUDA Test Development team, responsible for all aspects of quality assurance, including regression testing, release testing, test automation, and test development. We ensure the highest quality standards for every CUDA product. What you will be doing: - Design and implement functional/performance tests for CUDA products, like driver and library. - Automate CUDA tests, design test plans and integrate into automation testing infrastructure. - Triage test results, root cause test failures or performance drops, and drive through bugs to fix. - Develop scripts/tools and optimize workflow to improve efficiency and productivity. What we need to see: - MS or PhD degree from a leading university in computer science or a related field. - At least 3 years of relevant professional experience. - Excellent QA sense, knowledge, and experience in software testing. - Rich experience in test case development, tests automation and failure analysis. - Proficient programming and debugging skills in C/C++ and Python. - Comprehensive knowledge of Linux and Windows operating systems. - Experience in using AI development tools for test plans creation, test cases development and test cases automation. Ways to stand out from the crowd: - Excellent English communication and collaboration skills. - Strong understanding of CUDA, HPC, Gcov, VectorCAST, Coverity.
Senior AI Solutions Architect - Semiconductors
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 Senior Solutions Architect to support our Semiconductor accounts — the chip-design houses, EDA software vendors, semiconductor-equipment makers, and fabs adopting accelerated computing across chip design, verification, lithography, and manufacturing. In this role you will be a trusted technical advisor to EDA/CAD developers and customer engineering teams, embedding NVIDIA accelerated computing, computational lithography (cuLitho), and AI into design, verification, and manufacturing workflows. You will play a direct role in improving application performance, accelerating design and yield cycles, and establishing the technical foundation required for next-generation semiconductor systems. What you’ll be doing: - Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Semiconductor accounts (EDA vendors, chip designers, semiconductor-equipment OEMs, and fabs). - Work directly with EDA/CAD developers and customer design and manufacturing teams in a customer-facing setting. - Help developers GPU-accelerate and scale EDA workflows — place-and-route, circuit simulation, timing and power analysis, DRC/LVS, and verification — and computational lithography (e.g., NVIDIA cuLitho). - Apply ML/DL to semiconductor manufacturing: defect detection, inspection and metrology, yield optimization, and process control. - Analyze EDA and manufacturing application architectures and find opportunities for acceleration. - Provide feedback and collaborate with engineering, product, and research teams. - Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms. What we need to see: - MS/PhD in Electrical or Computer Engineering, Materials Science, Applied Physics, Computational Science, or a related technical field (or equivalent experience). - 4+ years in semiconductor design, EDA, or semiconductor manufacturing — chip design/verification, TCAD, lithography, or fab process/yield engineering — and/or AI/ML applied to these domains. - Familiarity with EDA flows and tools (e.g., Cadence, Synopsys, Siemens EDA) and/or computational lithography, TCAD, or inspection/metrology systems. - Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads. - Development experience using major AI frameworks (e.g., PyTorch, TensorFlow) for vision, ML, or manufacturing use cases. - Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters. - Familiarity with containers, numerical libraries, modular software design, version control, GitHub. - Experience designing, prototyping, and building complex AI/ML-based solutions for customers; able to reason across components such as data pipelines, models, compute, networking, and orchestration. - Solid written and oral communication skills and familiarity with collaborative environments. - Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment. Ways to stand out from the crowd: - Experience with computational lithography (NVIDIA cuLitho) or GPU-accelerated EDA flows. - Experience applying ML/DL to defect inspection, metrology, or yield and process optimization in a fab or equipment setting. - Development experience with NVIDIA software libraries and GPUs, including CUDA and CUDA-X libraries. - Experience with Kubernetes, distributed training, and large-scale inference. - Experience supporting or using PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages. NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you! NALASAHiring 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 July 20, 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 Circuit Design Engineer
We are now hiring a Circuit Design Engineer for Standard Cell Characterization. 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. NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are looking to grow our company and teams with the best people in the world. We're rapidly growing our research and development for Inference. We specialize in developing GPU-accelerated Deep Learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in Deep Learning and enabling breakthroughs in numerous areas. What you will be doing: - Work on the cutting edge processor design in deep submicron technologies, and on standard cell library design and characterization. Driving the concepts of the transistor level circuit design, modeling and performance analysis process. - Support and development of tools using Perl/Python. - We will have creative new insights to support existing tools and flows and develop new simulations to perform timing/power/noise/OCV evaluations. - Collaborate with cross function teams with regards to library issues. We will improve on our quality checks on the library work. What we need to see: - MS in Electrical or Computer Engineering or equivalent experience - 4+ years of experience is preferred. - We are looking for strong background in deep submicron process issues. - Deep understanding of the design, verification and characterization of standard cell libraries. Deep understanding on generating timing/power/noise/OCV views of the standard cells, validation of data and QA process. - Familiar with Liberty models and its application to digital implementation and signoff flows. - Hands-on experience running SPICE simulation, and capability to adapt to new simulation tools. - Strong proficiency in scripting language, such as, Perl, Tcl, Make, and automation methods/algorithms a certain plus. - We are looking for excellent team-work, communication and analytical skills. You shall be able to learn quickly, hard-working, and are results-oriented. - Having past standard cell library or IP characterization experience 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 July 20, 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 Signal and Power Integrity Engineer - Hardw...
We are now looking for a Senior Signal & Power Integrity Engineer! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. This is a dynamic team working with state of the art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! What you'll be doing: - Work on crafting creative Signal Integrity solutions to complex system design problems. - Modeling and Optimization of vias, connectors, sockets, breakouts and various system components in 3D EM tools. - System-level signal integrity simulations of high-speed NVlink 200Gbs+, USB-4, PCIe5, GDDR6, LP5X and other interfaces. - Constant improvements of SI models using data from lab measurements and/or modelling tool/methodology updates. - Substrate and board layout SI guidelines creation, review and post layout SI extractions. - Simulation automation, data gathering, analysis and visualization using JMP, MATLAB or similar tools. - Opportunity to work in a dynamic cross-functional role to optimize package, PCB, ASIC, mixed signal circuit. What we need to see: - BS/MS-Electrical Engineering or equivalent experience with 6+ years of industry experience. - Strong technical background in applied electromagnatics, transmission line theory and signal processing will be highly valued. - SI work on one or more signaling standards like PCI express, USB, SATA, HDMI, HBM, DDR5, GDDR6, LPDDR5X, etc. - Hands on use of 3-D modeling tools like ANSYS HFSS/Q3D, 2.5-D with ANSYS SIWAVE or similar and 2D such as Ansys2D. - Familiarity with a system level timing or loss budget including silicon, package and board impairments. - Familiarity with use of VNA, TDR, DSO, ParBERT and use of tools/applications like ADS, Ansys Designer, JMP, Matlab, Cadence Allegro will be a plus. Ways to stand out from the crowd: - Experience in interconnect electromagnetic model design for 200Gbps systems, particularly in backplane and midplane architectures. Hands-on expertise in characterizing and correlating high-speed connectors and cable assemblies in the lab (including using VNA). - Strong understanding of stamping, plating, and molding processes to effectively collaborate with mechanical and industrial engineers on design trade-offs. Knowledge of characterizing new LCP materials to develop accurate electrical component libraries. - Ability to conduct statistical analysis of connectors, cables, and cable assemblies to assess performance at production sites, enhancing data-driven decision-making. - Proficiency in analyzing connector product specifications including mechanical, environmental, electrical and SI testing requirements. - Knowledge of circuit design, board/pkg technology & design, link architecture, timing budget methodologies. 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 July 20, 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 Solutions Architect, AI - Accelerated Physi...
At NVIDIA, we believe that accelerated computing is key to solving the world’s most significant scientific and engineering challenges. We are looking for a Solutions Architect to join our Higher Education and Research Team, where you will serve as a technical partner to the visionaries shaping the future of discovery! In this role, you will be an integral part of a team supporting higher education universities and research institutes across the nation, with a focus on computational physics, engineering simulation, scientific AI, and high-performance computing. You will help researchers harness NVIDIA platforms to accelerate simulation, build trusted AI surrogates, train scientific foundation models, and unlock new workflows in areas such as fluid dynamics, multiphysics simulation, engineering design exploration, and physics-based modeling at scale. If reading this gets you excited and energized to help researchers solve hard computational physics and engineering problems, then we would love to meet you. What you'll be doing: - Partner with research universities and institutes to co-create innovative HPC and AI solutions using NVIDIA’s accelerated computing platform - Collaborate with engineering, product, and business teams to align NVIDIA’s technical roadmap with the evolving strategies and complex workflows of the scientific and engineering research community - Engage with developers and researchers to architect ground-breaking solutions in areas such as computational physics, multiphysics simulation, engineering design exploration, and the next generation of Scientific Foundation Models - Help researchers move from high-fidelity simulation data to AI-enabled workflows, including surrogate models, neural operators, physics-informed models, reduced-order models, differentiable simulation, and real-time inference - Profile and optimize the performance of scientific applications, AI training, and inference workloads so sophisticated research workflows reach their full potential on accelerated systems - Travel requirement up to 20% What we need to see: - BS, MS or PhD in Computational Physics, Engineering, Computer Science, Applied Mathematics, or a related field, or equivalent experience - 8+ years of hands-on experience in accelerated computing and knowledge of parallel computing with GPUs - Experience porting and/or optimizing scientific or engineering applications targeting GPUs - Strong fundamentals in programming and software design, especially in Python and C++ - Familiarity with computational physics or engineering simulation workflows, including numerical methods, model validation, uncertainty/error analysis, or simulation-data pipelines - Excellent knowledge of the theory and practice of AI at scale, especially as applied to scientific, simulation, or physics-based workloads - A dedication to clear and inclusive communication with a deep desire to partner with the academic community to help others succeed in their research goals Ways to stand out from the crowd: - Excellent GPU programming skills, including debugging, profiling, code optimization, performance analysis, and test design - Experience supporting HPC, AI, computational physics, engineering simulation, or scientific computing workflows. - Familiarity with NVIDIA scientific computing and AI tools such as PhysicsNeMo, NVIDIA Warp, PyTorch, JAX, or related frameworks - Experience building AI-enabled simulation workflows using neural operators, physics-informed models, graph neural networks, and/or reduced-order models. - A desire to learn and grow within an encouraging, forward-thinking community dedicated to solving the world’s most significant computational science and engineering challenges 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/ NALASAHiring 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 July 20, 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 Software Engineer - AI Inference
NVIDIA is the platform upon which every new AI‑powered application is built. We are seeking a Senior Software Engineer – AI Inference to advance open‑source LLM serving by contributing directly to upstream inference engines like vLLM and SGLang-ensuring they run best‑in‑class on NVIDIA GPUs and systems-and by improving the underlying stack that enables high‑throughput, low‑latency inference at scale. This is a hands-on role for an engineer who enjoys digging into performance bottlenecks, designing pragmatic runtime improvements, and shipping high‑quality changes that are broadly useful to the community and production deployments. What you'll be doing: - Contribute features, fixes, and optimizations upstream to vLLM/SGLang: author PRs, participate in reviews, write benchmarks/tests, and help drive designs to completion. - Implement and optimize inference‑runtime capabilities: batching and scheduling policies, streaming, request lifecycle management, and KV‑cache efficiency (paging/sharding) to improve throughput and tail latency. - Profile and improve hot paths across layers-from Python orchestration to C++/CUDA kernels-using data to guide optimization work. - Improve multi‑GPU inference performance and reliability: parallelism strategies, communication patterns, and resource utilization across NVIDIA platforms. - Build and maintain performance and correctness regression tests to prevent slowdowns and ensure stable behavior across model and hardware configurations. - Collaborate with model, platform, and SRE teams to translate production requirements into upstreamable solutions with strong operability and maintainability. What we need to see: - 5+ years building production software with solid systems engineering fundamentals and a track record of delivering performance or reliability improvements. - Experience with LLM inference/serving stacks (e.g., vLLM, SGLang) and an understanding of the tradeoffs that drive real production performance. - Strong programming skills in Python plus C++ and/or CUDA; ability to debug and optimize performance‑critical code. - Experience with profiling and performance investigation (microbenchmarks, flame graphs, GPU profiling) and a measurement‑driven mindset. - Familiarity with distributed systems concepts and concurrency (queues/schedulers, multi‑process/multi‑threading, scaling across GPUs/nodes). - Strong communication skills and comfort working with open‑source communities (issues, PR discussions, code review). - BS/MS in Computer Science, Computer Engineering, or related field (or equivalent experience). Ways to stand out from the crowd: - Open‑source contributions to vLLM, SGLang, PyTorch, Triton, NCCL, Dynamo or adjacent serving/runtime projects. - Shipped performance work such as improved attention/KV cache efficiency, speculative decoding, scheduler improvements, quantization-aware serving, or streaming latency reductions. - Experience building reproducible benchmarking and performance regression infrastructure for latency/throughput. - Systems performance background spanning memory bandwidth, kernel fusion, PCIe/NVLink effects, and network fabrics (e.g., InfiniBand). We are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward‑thinking and creative people in the world working for us. If you're creative and autonomous 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 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 July 20, 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 Software Engineer, AI Performance Analysis
NVIDIA GPU Architecture Group is seeking a senior software engineer to automate and optimize performance analysis workflows for AI training and inference workloads. You will not only perform analysis but also reshape how it's done, building tools and workflows that scale across a broad audience of engineers. NVIDIA is a world-class leader in AI workload optimization, and your work will push these boundaries even further! What you'll be doing: - Design and build performance analysis tools and workflows for AI training and inference workloads. - Understand how AI performance engineers work and translate their needs into scalable, intuitive tooling. - Develop integrations between profiling infrastructure and AI frameworks and workflows. - Collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads. - Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them. What we need to see: - M.S., or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience). 6+ years of relevant work experience - Deep knowledge of AI workloads, frameworks, and performance characteristics. - Experience building tools, workflows, or infrastructure used by other engineers. - Strong software development skills (Python, C++ preferred). - Ability to translate user requirements into scalable tooling solutions. - Up to date with AI-enabled tooling for software development and performance analysis. - Strong interpersonal skills for understanding engineer difficulties and working across multi-functional teams. Ways to stand out from the crowd: - Experience profiling or optimizing AI training or inference pipelines at scale - Background building developer tools or platforms for ML engineers - Contributions to open-source AI tooling or frameworks 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 July 20, 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.
Solutions Architect, Supercomputing
We are looking for a Solutions Architect to join a team to engage with customers, partners, and other NVIDIA software engineers to collaborate with developers and support applications and platforms that leverage NVIDIA technology that will be adopted across all industry segments. At NVIDIA, our Solutions Architects are drawn from elite developers and scientists who enjoy working with the latest in GPU and Networking hardware and software! NVIDIA’s platforms for machine learning, deep learning and high-performance computing have already made a major impact and are broadly used across leading companies and start-ups. Our success has been the result of a vertical focus on industry business development, building a strong developer ecosystem, and scaling out the business using a broad partner channel including Hardware manufacturers and Cloud Service Providers. We need a passionate, hardworking, and creative individual to help us pursue more of these opportunities in HPC, Machine Learning (ML), AI Physics, Foundation Modeling, Physical AI, and Agentic AI! This role requires becoming a trusted technical advisor and leader to our partners and customers who believe that deep learning, data science, and artificial intelligence is a new computing revolution and has the potential to transform industries. In addition, you will be the trusted advisor for the solutions architects on your team. A Solutions Architect is the bridge of technical expertise between our industry teams, our partners and customers. Dynamically engaging with internal developers, scientific researchers, data scientists, IT managers and senior leaders is an important part of the Solutions Architect role and will give you experience with a range of partners and concerns. This position requires a security clearance and U.S. citizenship. What you'll be doing: - Partner with our industry and account teams in a customer facing role to develop a keen understanding of customer goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs. - Document what you know and teach others. This can vary from building targeted samples, to writing white papers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard. - Be an industry leader with vision on integrating NVIDIA technology into AI Workloads and Workflows, HPC, and enterprise GPU and networking architectures for advanced applications both in the datacenter and at the edge. - Strategically partner with lighthouse customers and industry-specific solution partners targeting our computing platform. - We make heavy use of conferencing tools, but some travel is required for this role. Be empowered to find the best way to get your job done and do what it takes to make our partners and customers successful. What we need to see: - Bachelors degree in Engineering, Mathematics, Physics, Computer Science or equivalent experience. - 5+ years of work-related experience in data science or software development with knowledge of parallel computing with GPUs. - Background working with modern application deployment practices including but not limited to Slurm, Docker/Containers, and Kubernetes. - Experience with modern Generative AI and Agentic AI architecture and frameworks. - Strong written and oral communication skills with the ability to effectively collaborate with accounts, customers, management, and engineering. A big part of this role is educating our customers, whether that be through product roadmaps/presentations/briefings or hands-on engagement with developers. - Experience supporting customers/partners in technical engagements. - Strong organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects. - Strong analytical and problem-solving skills. Ways to stand out from the crowd: - Experience applying data science to industry problems. - Experience using GPGPU programming and design practices. - CUDA programming and optimization experience. - Background with network software development. - Experience with AI: Published record of thought leadership in a technical area or industry segment - Deep Neural Network, Machine Learning R&D - Agentic AI, surrogate Models, or foundation models. NALASAHiring 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 July 20, 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 Machine Learning Graphics Engineer, AI for...
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is searching for a world-class engineer in graphics and AI to join our neural graphics product team. If you agree with us that the most exciting thing about the AI revolution is applying it to solve real problems, this team will be an excellent fit for you! We are passionate about applications in generative AI, gaming, augmented reality, user-generated content, computer vision, and other areas, with the goal of improving visual fidelity, gameplay, or other domains within the gaming and pro-visualization markets. Working with other teams throughout the company, you will productize promising research, as well as develop new features through your own work. What you'll be doing: - Use AI for solving product problems in gaming and other interactive experiences. - Build upon the latest research to create new models and invent new ways of applying AI to advance neural graphics and gaming. - Create prototypes to demonstrate real-life applications of your ideas and to accelerate productization. - Keep up with the latest AI/DL research and collaborate with diverse teams (both internal and external to NVIDIA), including AI/DL researchers, hardware architects, and software engineers. - Participate in technology transfers to and from teams across NVIDIA. What we need to see: - Master's in computer science/engineering, Machine Learning, AI, and related fields (or equivalent experience) - 12+ years of machine learning / deep learning research or work experience - Knowledge of application areas such as real-time computer graphics, CV, and game development. - Expertise with programming systems such as Python, C+, CUDA, and deep learning frameworks such as TensorFlow and PyTorch. Very strong programming skills. - A proven track record of delivering complex products and technologies spanning multiple teams and functional areas. Intelligent machines powered by AI computers that can learn, reason, and interact with people are no longer science fiction. Image recognition and speech recognition — GPU deep learning has provided the foundation for machines to learn, perceive, reason, and solve problems. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is known as “the AI computing company.” Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 July 20, 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 and Machine Learning Specialist
We are hiring Senior AI / Machine Learning Engineers to compose, build, and operate production AI systems across classical machine learning, computer vision, large language models, and agentic workflows. You will work across the full AI engineering lifecycle, from initial development and evaluation to deployment, observability, and ongoing improvement. This role suits engineers who can switch easily between system architecture and hands-on implementation. It is for those who understand what it takes to make AI systems reliable at production scale. What you’ll be doing: - Lead the build and delivery of production AI systems across machine learning, computer vision, LLM, and agentic use cases. - Build AI applications and agents that use tools, complete multi-step workflows, maintain state, and operate safely in production. - Develop evaluation strategies, test suites, quality metrics, and production feedback loops for models and AI applications. - Build scalable architectures covering model serving, APIs, data flows, workflow orchestration, observability, security, and failure recovery. - Build durable, distributed workflows using platforms such as Temporal, Prefect, or comparable technologies. - Deploy, monitor, and continuously improve AI systems for quality, latency, efficiency, reliability, scalability, and cost. - Make informed technical decisions around model selection, inference architecture, context management, structured outputs, tool use, and infrastructure. - Establish effective development, deployment, and validation practices for services, models, workflows, and infrastructure And provide technical leadership through architecture reviews, build decisions, code reviews, mentoring, and engineering guidelines. What we need to see: - 5+ years of experience in machine learning engineering, AI engineering, software engineering, platform engineering, or a comparable production-focused role. - Bachelors degree - A solid history of advancing innovative AI or machine learning systems from prototype to production. - Extensive knowledge in one or more fields including classical machine learning, computer vision, NLP, generative AI, or LLM applications. - Strong system-design skills, including experience with distributed systems, data-intensive applications, and cloud infrastructure. - Practical understanding of production LLM inference, including latency and efficiency trade-offs, context windows, token usage, model selection, and cost management. - Experience working with containers, orchestration platforms, CI/CD, monitoring, observability, and production incident investigation. - Sound engineering judgment around scalability, reliability, security, maintainability, and operational complexity. - The ability to independently guide complex technical projects and make effective decisions in ambiguous environments. - Strong communication and collaboration skills, including the ability to explain technical trade-offs to engineers, product teams, customers, and other collaborators. Ways to stand out from the crowd: - Experience working with both traditional machine learning systems and contemporary LLM or agentic applications. - Excellent judgment about when agent-based approaches are appropriate—and when a simpler solution is more effective. - Experience making AI behavior measurable, observable, explainable, and safe in production. - Experience optimizing inference systems for performance, infrastructure efficiency, and operating cost. - A history of guiding engineers or heading cross-departmental technical projects. We are looking for engineers who care deeply about technical quality. They take ownership from building through production. They are motivated by the challenge of turning advanced AI capabilities into reliable products. 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 AI Solutions Architect - Industrial Enginee...
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 Senior Solutions Architect to support our Industrial Engineering accounts — the CAE, CFD, and FEA software vendors, engineering-simulation platforms, and industrial OEMs building the next generation of physics-based and AI-augmented engineering workflows on NVIDIA platforms. In this role you will be a trusted technical advisor to simulation and engineering software developers, embedding NVIDIA accelerated computing, Omniverse, and physics-ML into solver, simulation, and digital-twin pipelines. You will play a direct role in improving application performance, accelerating design and simulation cycles, and establishing the technical foundation required for next-generation engineering and digital-twin systems. What you’ll be doing: - Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Industrial Engineering accounts (CAE/CFD/FEA ISVs, simulation platforms, and industrial OEMs). - Work directly with engineering-software developers and customer simulation teams in a customer-facing setting. - Help developers GPU-accelerate and scale CAE/CFD/FEA solvers and structural, thermal, and fluid-dynamics workloads on NVIDIA accelerated computing and HPC platforms. - Apply physics-informed ML and surrogate modeling (e.g., NVIDIA PhysicsNeMo / Modulus) and NVIDIA Omniverse digital twins to compress design, simulation, and optimization cycles. - Analyze simulation and engineering application architectures and find opportunities for acceleration. - Provide feedback and collaborate with engineering, product, and research teams. - Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms. What we need to see: - MS/PhD in Mechanical, Aerospace, Civil, or Chemical Engineering, Computational Science, Applied Mathematics, Physics, or a related technical field (or equivalent experience). - 4+ years working in CAE/CFD/FEA or computational engineering — numerical simulation, solver development, or HPC-based engineering analysis. - Hands-on experience with commercial or open-source simulation tools (e.g., Ansys, Siemens Simcenter, Altair, COMSOL, Cadence Fidelity CFD, OpenFOAM, LS-DYNA, Abaqus). - Strong grounding in numerical methods (FEM/FVM/spectral), linear algebra, and the mathematics behind physics solvers. - Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads. - Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters/schedulers (e.g., Slurm). - Familiarity with containers, numerical libraries, modular software design, version control, GitHub. - Experience designing, prototyping, and building complex solutions for customers; able to reason across components such as data pipelines, solvers, compute, networking, and orchestration. - Solid written and oral communication skills and familiarity with collaborative environments. - Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment. Ways to stand out from the crowd: - Experience GPU-accelerating CFD/FEA solvers, or developing physics-ML and surrogate models (NVIDIA PhysicsNeMo/Modulus, physics-informed neural networks). - Experience with NVIDIA Omniverse, OpenUSD, and digital-twin workflows for industrial and engineering simulation. - Development experience with NVIDIA software libraries and GPUs, including CUDA and CUDA-X math libraries (cuBLAS, cuSPARSE, cuDNN). - Experience with Kubernetes, distributed training, and large-scale inference. - Experience supporting or using PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages. NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you! NALASAHiring 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 July 20, 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 Applied AI Engineer
NVIDIA has been transforming accelerated computing with innovation that’s fueled by great technology—and amazing people. As part of Nvidia's applied AI team for chip design, you will have the opportunity to tap into the unlimited potential of AI and change the landscape of the chip industry. Our team operates at the intersection of research, engineering, and product development, transforming innovative ideas and research breakthroughs into real-world solutions. You will collaborate closely with researchers to design and scale agents - enabling them to reason, plan, call tools and code just like human engineers. You will work on building and maintaining the core infrastructure for deploying and running these agents in production, powering all our agentic tools and applications and ensuring their seamless and efficient performance. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation. What you'll be doing: - Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools. - Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale. - Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence. - Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization. What we need to see: - MS or higher degree (or equivalent experience) in Computer Science, Engineering, AI, or a related technical field, with 5+ years of hands-on software engineering experience building production-grade software systems, and demonstrated experience shipping AI/LLM-powered applications, agents, or automation workflows into real production environments. - Strong Python engineering skills are preferred, with the ability to design, prototype, and productionize AI-enabled services, APIs, integrations, automation workflows, and internal tools. - Practical experience building LLM-powered agents or agentic workflows, with hands-on use of Claude Code, OpenAI Codex, Cursor, GitHub Copilot, or equivalent coding agents to improve real software development workflows. - Solid software engineering fundamentals and production mindset, including system design, API design, testing, CI/CD, code quality, observability, security, databases, containers, and distributed or event-driven systems. - Ability to identify repetitive, high-friction, or knowledge-intensive workflows and turn them into practical AI-enabled tools, automations, or assistants that improve productivity and operational efficiency. - Demonstrated end-to-end ownership of engineering solutions, from architecture and development to deployment, integration, and ongoing operations/support. - Excellent communication skills and a collaborative, proactive approach. Ways to stand out from the crowd: - Strong ability to connect AI applications and agents with existing systems, services, databases, documentation, codebases, and enterprise workflows in a secure, reliable, and maintainable way. Experience with emerging integration patterns such as MCP, Skills, or similar frameworks 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 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 July 21, 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.
Principal Platform Software Engineer - RAS
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We are looking to grow our company and establish teams with the most thoughtful people in the world. NVIDIA GH200 superchip provides performance and productivity required for strong scaling for HPC and generative AI workload. Scale out is inherent to the design of this massive superchip. We are looking for expert engineers to come and help design rack level solutions for next generation scaling AI supercomputing platforms. Join us at the forefront of technological advancement. What you will be doing: - Drive next generation fleet management solutions for scaling AI infrastructure using GPUs and Grace solution from Nvidia. Work with customers, product management and other architects to narrow down on requirements for implementation to ensure speed of light product development. - Bring up clarity on architecture for fleet health monitoring and fault-remediation solution at scale. Work with customers and other architects, understand their requirements on health monitoring, making best use of available capabilities in-band as well as out of band. Detailed architecture, do POCs to validate architecture. - Educate customers about product architecture and take feedback to make necessary changes. Write architecture specs, design documents and own end to end delivery of product by working across the teams. Do code review for the code produced because of architecture specs. - Ensure product is properly tested by working with the development team to enhance unit testing and proper test plan in place. - Drive product life cycles with QA teams to productize the code and be responsible as a product owner. - Articulate requirements as part of Jira and bug management tools and work out an end-to-end execution plan in collaboration with other managers. - Contribute to all phases of product development, from product definition, architecture, and design, through implementation, debugging, testing and early customer support. What we need to see: - BS, MS, or PhD in EE/CS or related field of education (or equivalent experience). - 15+ years hands-on coding experience - Strong knowledge of time series databases like Influxdb & Prometheus. Strong knowledge of building and consuming REST APIs (Redfish is big plus). Strong knowledge of telemetry visualization solutions like Grafana & Influx. Strong knowledge of firmware architecture, optimize firmware for low latency APIs. Strong knowledge of analyzing algorithms for time & space complexity and project system resource requirements. - Proven record of solutions for scalability - Strong and demonstrable skill in C/C++ and Python - Experience programming and debugging skills for server platforms. - Experience in SCM (e.g., Git, Perforce) and project management tools like Jira. - You should possess excellent written and oral communication skills, excellent work ethics, a great sense of teamwork, 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 complicated problems and hands on with coding. Ways to stand out from the crowd: - Experience building telemetry collection & analysis engines. Experience with Redfish. Experience with notification systems like PagerDuty. - Active Open Compute (OCP) and DMTF contributor in relevant areas. Hands on with x86 or ARM system architecture. - Familiarity with Confidential Compute. Experience with ML and multi-variable optimization techniques. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you! 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 July 21, 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.
Solutions Architect, Energy OT and Industrial AI
Energy lies where AI meets the physical environment. NVIDIA's energy team aids operators in power generation, oil & gas, grid, and renewable fields as they progress from AI pilots to large-scale adoption — integrating secure, accelerated AI within control rooms, plants, substations, and field environments that uphold global operations. This role emphasizes that concluding step, converting NVIDIA's AI Factory, Omniverse, edge, and cybersecurity platforms into concrete results with our clients and collaborators. We are looking for an Energy OT / Industrial AI Solutions Architect to work with customers, partners, and NVIDIA engineers to bring AI into critical energy settings. This position links NVIDIA's AI platforms with workflows in control rooms, field operations, asset performance, and grid-edge that energy clients use. You will solve the last-mile deployment challenge to ensure secure and reliable AI across the energy value chain. This includes power generation, oil & gas and surface operations, transmission and distribution/grid, and renewables. You will apply NVIDIA technology and Python in operational-technology (OT) and industrial control system (ICS) environments. NVIDIA’s accelerated-computing platforms have already made a strong impact with top energy operators, utilities, and OEMs! We seek a curious, collaborative, and creative individual to advance work in industrial digital twins, edge AI, OT cybersecurity, generative and agentic AI, forecasting, and accelerated simulation. This role requires becoming a trusted technical advisor linking our industry teams, partners, and customers. Engaging with internal developers, researchers, data scientists, and senior leaders is vital and offers opportunities to work with diverse partners and challenges. What you will be doing: - Partner with our industry and account teams to understand customer goals, strategies, and technical needs. Define and deliver high-value, GPU-accelerated AI solutions for energy operations that meet these needs. - Develop industrial digital twins for plants, assets, and grids using Omniverse, OpenUSD, and PhysicsNeMo. - Implement predictive asset maintenance and asset-performance management solutions. - Deploy real-time AI at the edge for field, substation, and remote-site monitoring using Jetson/IGX and Metropolis. - Improve OT/ICS cybersecurity and secure remote access with Morpheus and BlueField. - Develop generative and agentic AI copilots for control-room and field workflows. - Perform forecasting and rapid simulation for power systems, subsurface, and process engineering. - Build industry direction by integrating NVIDIA technology into AI, HPC, and enterprise GPU and networking architectures for energy applications. - Strategically partner with flagship customers and industry-specific solution partners targeting our computing platform. - Collaborate primarily through virtual tools, with up to 20% travel required, and be empowered to find the best way to make our partners and customers successful. What we need to see: - MS or PhD in Electrical or Power Systems Engineering (or Chemical, Mechanical, or related engineering), Computer Science, Applied Mathematics, Physics, or equivalent experience. - Strong practical understanding of one or more energy sectors and their operational technology. Experience includes OT/ICS and control systems like SCADA, EMS/ADMS/DERMS, DCS, and PI historians. Familiar with operational tasks such as asset-performance management and predictive maintenance. - Experience with energy modeling and simulation tools — power-system tools such as pandapower, OpenDSS, GridLAB-D, MATPOWER/PYPOWER, PSS®E, PSCAD, PowerWorld, DIgSILENT PowerFactory, or MATLAB/Simulink. - Ability to transform energy and OT challenges into GPU-accelerated and AI workflows using NVIDIA's accelerated-computing and AI stack. - Familiarity with grid and industrial data models, standards, and protocols. - Familiarity with energy operations across the value chain — generation, grid operations and planning, interconnection, ISO/RTO markets, and field/surface operations — and the reliability and security regulatory environment. - At least 4 years working in power systems, industrial/OT engineering, data science, or software development, or in comparable positions, demonstrating strong Python ability and understanding of GPU parallel processing. - Experience with modern Deep Learning software architecture and frameworks and the Python data-science ecosystem. - Comfortable with modern application-deployment practices such as Docker/Containers and Kubernetes, including deployment to the edge. - Excellent communication skills — able to explain complex technical trade-offs to both engineers and executive partners. Strong problem structuring and self-direction help drive ambiguous projects involving multiple interested parties to results. Ways to stand out from the crowd: - Applied data science and machine-learning R&D on power-systems, grid, or industrial-asset data. - Creative generation of synthetic data to augment unusual energy and industrial datasets and stress-test models. - Experience with network software development, including NVIDIA BlueField DPUs. - Experience deploying AI in OT/ICS or industrial environments. - Background with Agentic coding practices. 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 July 21, 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.
Global Account Manager – AI and Accelerated Comput...
We are looking for a Global Account Manager (GAM) to be part of the Lenovo OEM team to drive adoption, integration of NVIDIA AI Software at Lenovo Corporation. We are seeking an expert, technically astute sales professional with a track record selling sophisticated solutions to large organizations. This position requires collaboration with Lenovo and NVIDIA platform development teams covering hardware, software, delivery and support, product managers, product marketing, and GTM teams. We highly value creativity, energy and a drive to succeed in a challenging, fast paced environment! What you will be doing: - Develop deep technical understanding of the NVIDIA Agentic AI Platform inclusive of GPU, DPU, CPU, reference architectures, software, licensing models. - Understand Lenovo’s product stacks including Data Center, Client, Edge, Networking, and Storage. Identify areas to integrate NVIDIA AI, Software, SDKs, Libraries. - Package NVIDIA accelerated computing and AI as Lenovo solutions, help co-market, co-sell in DC, Cloud, and Enterprise segments via Direct, VAR, Distribution, GSI sales channels. - Build thought leadership for joint solutions by participating in industry and customer events. - Expand partnerships with NVIDIA AI ecosystem and develop, deploy 3-way go to market. What we need to see: - Bachelor’s degree in computer science or business or equivalent experience. - 12+ years of shown success with software products sales, integration with large organizations - Excellent presentation, communication skills. - Confirmed understanding of AI software integration, commercialization, and sales - Knowledge of cloud native environments such as Kubernetes, Docker, OpenShift, microservices, etc. - Comparative understanding of cloud, on-prem and hybrid cloud environments. - A strong curiosity about understanding new technologies, adept at conveying value to business executives and software development leaders. - Proven track record working with a matrixed team including product, engineering, DevOps, IT. Ways to stand out from the crowd: - Experience selling software with the Lenovo product portfolio - Understanding of accelerated computing, data science, machine learning, and AI deployment at scale. - Experience working with ISVs and System Integrators to accelerate solution deployment - Consistent record embedding SW and building solutions in partnership with ISV ecosystem - Demonstrated ability to provide thought leadership, think strategically, act independently, and optimally communicate vision (both written and verbal) 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. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 21, 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 Software Engineer, AI Agent Platforms
NVIDIA is spearheading the AI revolution and the creation of state-of-the-art accelerated compute platforms for global utilization. Our team's mission is to put AI at the center of engineering across NVIDIA's networking architecture organization. We build AI agents that solve real engineering problems, the platforms that make them reliable, and we lead the organization's AI adoption, making sure it happens fast and with strong engineering practices. Powered by the AI revolution we are changing how hardware architecture work happens! We strive to define and implement this new agentic architecture, and we are seeking a software engineer for our agentic AI team. If you are excited to work at the frontier of AI agents and want your work to multiply the output of hundreds of engineers, we want to hear from you. What you'll be doing: - Build AI agents that solve real engineering problems across the networking stack — and ship them to daily use. - Design and build the platforms that make those agents reliable: typed tool surfaces, cloud services, and the systems behind them. - Work broadly across networking architecture teams to identify high-impact AI use cases and turn them into working solutions. - Drive rapid and responsible AI adoption across the organization: establish best practices, guardrails, and evaluation methods so teams embrace agentic workflows with confidence. - Build evaluation pipelines that measure and improve AI-agent behavior on real production workloads. What we need to see: - BSc in Computer Science or a related field, or equivalent experience. - 5+ years of relevant practical experience in software development, including working on a large-scale software product. - Advanced, demonstrable use of AI and agentic workflows in your daily engineering work well beyond standard coding assistant usage. - A fast learner, comfortable moving across codebases, domains, and teams. - A drive for end-to-end ownership and strong communication skills. Ways to Stand Out from the Crowd: - Cloud-native development experience (containers, Kubernetes, CI/CD pipelines). - Background in computer networking or HPC. NVIDIA has some of the most forward-thinking and hardworking people in the world working for us. If you are a creative and autonomous engineer with a real passion for technology, we want to hear from you.
Distinguished AI Researcher, Advanced Development...
NVIDIA has been defining computer graphics, PC gaming, and accelerated computing for more than 25 years. With an outstanding legacy of innovation, driven by phenomenal technology and extraordinary people, NVIDIA is looking for a Distinguished Engineer to help shape the future of AI infrastructure. As part of our advanced development and research efforts, you will drive technical vision and innovation across the AI software stack, spanning GPU computing, RDMA, NVLink, storage, and large-scale distributed systems. You will research next-generation system designs, influence product and platform direction, and help define how massive-scale AI environments are built, optimized, and operated through hardware-software co-design. What you’ll be doing: - Research, define, and drive co-design solutions across AI software stacks involving GPU computing, RDMA networking, NVLink interconnects, storage, and large-scale distributed infrastructure - Lead deep technical investigations and proof-of-concept development in areas related to distributed AI, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design - Work closely with multiple teams across NVIDIA to advance next-generation AI infrastructure technologies and influence cross-stack co-design decisions - Analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and storage layers to improve performance, scalability, and efficiency - Guide the design of environments that support massive-scale AI training and inference workloads in production What we need to see: - M.S. or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience - 20+ years of industry experience in systems design, distributed systems, system software, or related fields - Chief Scientist, CTO, or equivalent senior technical leadership experience in smaller companies is highly desirable - Deep background in distributed systems, parallel computation, networking, storage, virtualization, and memory management - Experience building, scaling, and supporting environments for massive AI workloads - Strong understanding of large-scale systems operational aspects, including performance, reliability, scalability, and supportability - Excellent communication, collaboration, and technical leadership skills in a multi-national, multi-time-zone environment Ways to stand out from the crowd: - Proven research track record in AI systems, large-scale infrastructure, or advanced systems co-design - Deep expertise in GPU systems, RDMA, NVLink, and storage technologies for AI and HPC workloads - Strong record of cross-functional influence spanning hardware, system software, networking, and infrastructure 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, autonomous, and excited to drive the future of AI infrastructure at scale, 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 Technical Program Manager – Windows Client...
NVIDIA is leading the next era of AI computing, bringing AI from the cloud to local devices. The Windows Client AI team develops the software platform that enables developers, enterprises, and creators to build and run AI applications on NVIDIA client platforms, including GeForce RTX PCs, RTX PRO workstations, RTX Spark, DGX Spark, and DGX Station. We are looking for a highly technical Senior Technical Program Manager to lead the execution of NVIDIA's Windows Client AI software platform. In this role, you will work closely with engineering, product management, architecture, developer technology, and strategic partners to deliver the next generation of AI experiences on Windows. You will drive complex cross-functional programs spanning AI frameworks, inference runtimes, model optimization, Windows integration, developer tools, and AI applications. This is a highly visible role requiring technical depth, exceptional execution, and the ability to influence engineering decisions across multiple organizations. What you'll be doing: - Drive end-to-end execution of the Windows Client AI software roadmap across globally distributed engineering teams, ensuring alignment, transparency, and predictable delivery. - Partner with product management and architects to translate product strategy into engineering plans, milestones, and successful releases with measurable outcomes. - Lead cross-functional programs influencing technical direction, trade-offs, and prioritization spanning AI frameworks, inference runtimes, model optimization, Windows integration, SDKs, and AI applications. - Work closely with engineering teams to identify technical risks, resolve cross-team dependencies, and drive execution from concept through release. - Collaborate with Microsoft, OEMs, ISVs, and internal teams to enable new AI capabilities across NVIDIA client platforms. - Drive planning and execution for emerging AI technologies, including LLMs, multimodal AI, AI agents, model optimization, and hybrid AI applications. - Communicate program status, milestones, risks, and key decisions to engineering leadership and executives. - Champion engineering best practices in planning, release management, and program execution across globally distributed teams. What we need to see: - BS/MS in Computer Science, Computer Engineering, or equivalent experience. - 8+ years of experience leading complex technical programs in software engineering, AI/ML infrastructure, developer platforms, or systems software. - Strong understanding of modern AI software stacks, including deep learning frameworks, inference engines, and AI developer workflows. - Excellent communication, organizational, and cross-functional leadership skills with a proven ability to influence across organizations. - Strong analytical and problem-solving skills, with experience driving large-scale software programs from concept to release. Ways to stand out from the crowd: - Software engineering background with experience in C++, Python, or AI/ML systems. - Familiarity with modern AI inference technologies such as TensorRT, vLLM, PyTorch, ONNX Runtime, DirectML, or llama.cpp. - Experience with LLMs, multimodal AI, agentic AI, model optimization, or GPU acceleration. - Knowledge of Windows platform technologies, GPU architecture, CUDA, or NVIDIA AI software. - Experience collaborating with Microsoft, OEMs, ISVs, or contributing to open-source AI projects. NVIDIA is widely considered one of the technology world's most desirable employers. We have some of the most forward-thinking engineers and researchers solving the hardest problems in AI computing. If you're passionate about AI, enjoy solving complex technical challenges, and thrive in a collaborative environment, we'd love to hear from you.
AI Developer Technology Engineer
NVIDIA is looking for a passionate, world-class computer scientist to work in its Compute Developer Technology (Devtech) team as an AI Developer Technology Engineer. Artificial intelligence, the dream of computer scientists for over half a century, is no longer science fiction. And in the next few years, it will transform every industry. Soon, self-driving cars will reduce congestion and improve road safety. AI travel agents will know your preferences and arrange every detail of your family vacation. And medical instruments will read and understand patient DNA to detect and treat early signs of cancer. Where engines made us stronger and powered the first industrial revolution, AI will make us smarter and power the next. What will make this intelligent industrial revolution possible? A new computing model — GPU deep learning — that enables computers to learn from data and write software that is too complex for people to code. What you will be doing: - Study and develop cutting-edge techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures. - Work directly with key customers to understand the current and future problems they are solving and provide the best AI solutions using GPUs. - Collaborate closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the design of next-generation architectures, software platforms, and programming models. What we need to see: - A Masters degree or PhD in an engineering or computer science related discipline or equivalent experience and 2+ years of relevant work or research experience. - Strong knowledge of C/C++, software design, programming techniques, and AI algorithms. - Firsthand work experience with parallel programming, ideally CUDA C/C++. - Strong communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills. - Some travel is required for conferences and for on-site visits with developers. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous computer scientist with a genuine passion for parallel computing? If so, we want to hear from you. Come, join our AI Compute DevTech team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. 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 Director, Enterprise Software Engineering a...
Lead the transformation of enterprise software engineering in an AI-first world. This role defines the strategy, architecture, and operating model for an intelligent software ecosystem where commercial SaaS, custom software, AI agents, and automation work together to accelerate business outcomes. You will shape how the enterprise makes Build, Buy, and Agent decisions while establishing the engineering foundations, governance, and AI-native platforms that power the next generation of enterprise software. What You'll be doing: - Define and execute the long-term strategy for enterprise software engineering in an AI-first, agentic world. - Lead a global engineering organization across Enterprise Applications, AI Engineering. - Drive the company's Build, Buy, and Agent strategy, balancing innovation, speed, cost, and long-term architectural direction. - Architect and modernize enterprise platforms by integrating commercial SaaS, custom software, APIs, AI agents, and intelligent automation into a unified ecosystem. - Establish world-class engineering practices across software engineering, platform engineering, SRE, DevSecOps, security, reliability, and developer experience. - Lead enterprise-wide modernization initiatives, including cloud transformation, AI adoption, platform consolidation, and engineering modernization. - Build and develop high-performing engineering leaders while fostering a culture of technical excellence, innovation, accountability, and continuous learning. - Partner with executive leadership and strategic technology providers to shape technology strategy, influence product roadmaps, and drive business impact. What We Need to See: - Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field (or equivalent experience); Master's degree preferred. - 18+ years of software engineering experience, including 10+ years leading globally distributed engineering organizations through enterprise-scale transformation. - Deep expertise in modern software engineering, cloud-native platforms, AI-enabled systems, and a strong track record of making strategic Build, Buy, and Agent decisions. - Proven success building high-performing engineering organizations, influencing executive stakeholders, and delivering secure, scalable, and reliable enterprise platforms. Ways to Stand Out from the crowd: - Experience building and scaling AI-native or agentic platforms that transformed enterprise productivity or business operations. - Demonstrated track record of delivering step-change improvements in engineering productivity, developer experience, or business outcomes through technology innovation. - Recognized technical leader through patents, open-source contributions, publications, conference speaking, or leadership within the AI engineering community. - Passion for building exceptional engineering cultures and developing future technology leaders. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 340,000 USD - 517,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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.
Solutions Architect — Power and Utilities, AI Grid...
Join us at NVIDIA, where we are pushing the boundaries of what's possible in the power and utilities sector through innovative AI and accelerated computing solutions. As a Utilities and Energy Sector / Grid AI Solutions Architect, you will work with customers, partners, and fellow NVIDIA engineers to build AI applications and platforms that support grid modernization, simulation, interconnection acceleration, forecasting, resilience, and flexible load orchestration. You will bring to bear NVIDIA technology and Python across the energy and utility industries, impacting transmission and distribution system operators, generation owners, and grid-software vendors. Are you passionate, dedicated, and creative? Our team seeks a member to advance opportunities in grid simulation, forecasting, optimization, and applied AI. You will become a trusted technical advisor, connecting our industry teams, partners, and customers. Engaging with internal developers, researchers, data scientists, and senior leaders is a core part of the role, offering exposure to a wide range of partners and challenges! What you will be doing: - Partner with our industry and account teams to understand customer goals, strategies, and technical needs, and to define and deliver high-value, GPU-accelerated grid solutions that meet them. - Build and prototype solutions for specific grid problems such as interconnection-study and queue acceleration, load and renewable-generation forecasting, DER/DERMS orchestration, power-flow and contingency analysis at scale, predictive asset maintenance, wildfire and grid-resilience analytics, and data-center demand flexibility (e.g., EPRI DCFlex). - Help develop industry direction by integrating NVIDIA technology into AI, HPC, and enterprise GPU and networking architectures for grid applications. These range from control-center and planning workloads in the datacenter to real-time analytics at the grid edge and substation. - Strategically partner with flagship customers and industry-specific solution partners targeting our computing platform. - Collaborate primarily through virtual tools, with up to 20% travel required. What we need to see: - MS or PhD in Electrical or Power Systems Engineering, Computer Science, Applied Mathematics, Physics, or related experience (or equivalent experience). - Extensive practical understanding of the power and utilities sector and power-system basics, with direct experience in grid applications and tasks including SCADA/EMS/ADMS/DERMS, power-flow and state estimation, contingency and stability analysis, load and renewable forecasting, and grid asset management. - Hands-on experience with power-system modeling and simulation tools such as pandapower, OpenDSS, GridLAB-D, MATPOWER/PYPOWER, PSS®E, PSCAD, PowerWorld, DIgSILENT PowerFactory, or MATLAB/Simulink, including real-time and hardware-in-the-loop platforms such as RTDS, OPAL-RT, or Typhoon HIL. - Ability to translate power-system problems into GPU-accelerated workflows using NVIDIA's accelerated-computing and AI stack (CUDA, RAPIDS/cuGraph, cuOpt, Modulus, Omniverse, Earth-2, and Triton/TensorRT). - Familiarity with grid data models, standards, and protocols — CIM (IEC 61970/61968), IEC 61850, DNP3, and OPC UA — along with utility data systems like OSIsoft/AVEVA PI historians and Esri ArcGIS Utility Network. - Familiarity with grid operations and planning, interconnection, ISO/RTO markets, and the NERC/FERC regulatory environment. - Over 4 years of professional experience in power-systems engineering, data science, or software development — or similar background — including solid Python skills and familiarity with GPU parallel computing. - Experience with modern Deep Learning software architecture and frameworks (e.g., PyTorch, TensorFlow) and the Python data-science ecosystem (NumPy, pandas, RAPIDS). - Comfortable with modern application-deployment practices such as Docker/Containers and Kubernetes. Ways to stand out from the crowd: - CUDA and GPGPU programming and optimization experience. - Applied data science and machine-learning R&D on power-systems or grid data — load/price forecasting, renewable integration, outage prediction, anomaly detection, or graph neural networks on grid topology. - Creative generation of synthetic data — synthetic load profiles, grid topologies, or fault scenarios — to augment unusual grid datasets and stress-test models. - Experience with network software development. With competitive salaries and a generous benefits package, NVIDIA is recognized as one of the technology world’s most sought-after employers. This role offers a chance to make a broad impact at NVIDIA by advancing innovation within our power and utilities sector. Are you inventive, diligent, committed, and driven? Do you enjoy tackling challenges? 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 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 July 24, 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 Data and AI Solutions Engineer
NVIDIA is a world leader in computer graphics, artificial intelligence, and accelerated computing. For over 30 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. NVIDIA’s Networking System Product Engineering organization is looking for a S enior Data & AI Solutions Engineer - high-agency, self-directed Data & AI Solutions Engineer to partner with engineering teams and transform data, BI, automation and agentic AI into measurable engineering productivity gains. What you’ll be doing - Work closely with engineers, managers, and cross-functional teams to understand complex engineering domains, identify bottlenecks, and build practical solutions that improve decision-making, execution speed, and operational quality. - Develop and deliver production-grade tools, automated workflows, and agentic AI solutions from concept through deployment. - Run fast, high-quality proof-of-concepts on emerging AI and agentic technologies, and productize successful ones. - Implement data flywheels that continuously improve quality through telemetry, benchmarking, automated evaluation, and structured feedback loops. - Collaborate and contribute ideas and code to Product Engineering's evolving data infrastructure. - Improve data quality, integrity, governance, metric definitions, and usability across engineering domains. - Train and enable engineers, managers, and stakeholders to use data, BI, and AI tools effectively What we need to see - B.Sc or M.Sc in Computer Science, or related field, or equivalent experience. - 12+ years of proven experience building and deploying production software, data products, internal tools, or engineering productivity platforms and 2+ years of experience building AI-enabled or agentic systems, including tools & skills, RAG pipelines, persistent memory, and evaluation infrastructure. - Hands-on development experience with Python, full-stack software development, SQL and NoSQL databases, cloud environments, and internal tool development. - Extensive experience utilizing coding agents for development. - A proactive, high-agency builder who deciphers complex domains to deliver pragmatic, production-grade AI and data solutions that drive measurable engineering productivity.An adaptable expert who masters the intersection of software engineering and agentic AI, taking full ownership of the lifecycle from messy data debugging to cross-functional leadership. - Excellent collaboration skills, with the ability to influence cross-functional partners, build positive relationships, and communicate complex concepts clearly to both technical and business audiences. - Demonstrated commitment to continuous learning and development. Ways to stand out from the crowd - Background in product engineering, hardware engineering, networking, semiconductors, or complex engineering organizations - Evidence of meaningful open-source contributions, including core commits, maintainership, widely adopted libraries, or public technical artifacts demonstrating system-level depth 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.
Solution Architect - Telco AI
We are looking for a Solution Architect for the Telecommunications Industry team with domain specific knowledge and experience in AI and telecom operation. At NVIDIA, our Solution Architects are drawn from best-in-class engineers, architect, developers, and scientists who enjoy working with the latest technologies in data analytics and AI/ML/DL. NVIDIA platforms are broadly used across leading academic research centers, telecommunication and cable providers, industry software vendors and ecosystem start-ups. We need a passionate, hard-working, and creative individual to become a trusted technical who believes that accelerated computing, deep learning, advanced data science, and artificial intelligence is a new computing revolution and has the potential to transform the entire telecommunication domain. What you will be doing: - Document and demonstrate advancements in accelerated computing & AI applications through targeted trainings, sharing sessions, whitepapers, blogs, and wiki articles. - Realize our vision by introducing NVIDIA technology in telecommunication applications for network management & operation, and for cloud and edge computing (NFV). - Develop a keen understanding of customer’s goals and needs, deliver high-value solutions, and support technical trials, proof-of-concepts and customer adoption. - Lead technical project aspects of complex deployments, including design-in opportunities and responding to RFP/RFI proposals for AI software integration, or edge / cloud / datacenter deployments. What we need to see: - MS or PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields - 5+ years of relevant experience in telecommunication industry, networking hardware, networking software system development, or systems engineering or equivalent experience. - Expertise in data analytics and developing AI solutions for telco networks, or for enterprise IT/OT. - Good understanding of telco, cloud, or enterprise IT/OT (management and workload orchestration on cloud-native platforms), and experience in cloud-native application deployment. - Strong analytical and problem-solving skills with an ability to switch between high-level systems view and low-level design. - Ability to work in a team and to take a technical leadership in a project. - Good interpersonal skills (written and oral) and intellectual honesty. Ways to stand out from the crowd: - Relevant experience in 5G/6G network architecture and understanding of AI advantages for RAN. - Experience with NVIDIA AI platform and tools, and AI for RAN. - Strong time-management and organization 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 hardworking people in the world working for us. Are you a creative and autonomous computer scientist with a genuine passion for parallel computing? If so, we want to hear from you. Come, join our AI Compute DevTech team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. 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. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5.
Senior Customer Technical Program Manager - AI Dat...
At NVIDIA, we are at the forefront of AI and accelerated computing, redefining the world's largest industries and creating a profound impact on society. As part of the Customer Program Management Team, you will lead strategic technical programs with Cloud Service Providers (CSPs), driving the deployment of NVIDIA’s innovative AI infrastructure. This role offers a groundbreaking opportunity to work with brand-new technologies, such as the powerful NVIDIA GB300 NVL72 platform, delivering unmatched data center-scale performance. What you'll be doing: - Leading execution and technical engagement directly with CSPs and their ODM/OEM partners. - Integrating datacenter tools and operationalizing processes for AI factory build-out, resolving any blocking issues to keep projects on track. - Ensuring reliable assembly of groundbreaking AI infrastructure platforms by working closely with CSP’s ODMs or OEMs to meet specified metrics and schedules. - Assembling and guiding cross-functional teams, ensuring alignment and execution excellence. - Providing technical direction on server system building in collaboration with subject matter experts, and managing project timelines by proactively resolving blockers. - Ensure timely delivery of customer-specific features and production deployment. - Communicate program status, risks, and insights to senior leadership. What we need to see: - Demonstrated experience in program/project management involving direct interaction with customers. - 8+ years of experience managing programs and projects involving direct engagement with customers. - Strong leadership skills in global, matrixed environments. - Bachelor’s degree or equivalent experience in Computer Science, Engineering, or a related field. - A solid track record of successfully managing complex, large-scale datacenter projects. - A willingness to continue learning new skills and growing capabilities as NVIDIA ventures into new markets. Ways to stand out from the crowd: - Strong customer facing experience - Deep experience leading technical programs for CSPs. - Hands-on expertise in large-scale compute server build and deployment. - Strong cross-functional teamwork across globally distributed 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 in the world working for us. If you're creative, collaborative, 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 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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 Tools Development Engineer – Machine Learni...
This role within Deep Learning Focus Group is strongly technical, responsible for building DL/AI based solutions for validation of NVIDIA GPUs. For e.g. GPU Render Output Analysis (Video, Images, Audio) and complex problems like Intelligent Game Play Automation. This person would need to analyze/understand the challenges from stakeholders of various groups, design & implement DL solutions to resolve them. We are specifically looking for expertise in the following key areas: Game play automation using deep learning (DL) and artificial intelligence (AI) techniques, with a focus on research and application in the gaming industry.The candidate should be proficient in the following DL techniques: - Deep Reinforcement Learning (DRL) and Imitation Learning - Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs) - Generative AI and Diffusion Models Prior experience or research in AI-driven bots, In-Game Movement Automation, and Player Behavior Prediction are highly desirable. Knowledge in using AI development tools for test plans creation, test cases development and test cases automation. What you'll be doing: - Build Intelligent Gameplay Automation & Agentic Workflows: Design and deploy advanced gameplay agents using computer vision, reinforcement learning, imitation learning, and LLM/VLM-based agents, leveraging state-of-the-art tools like Codex and Claude. - Drive ML-Driven QA & Defect Detection: Apply ML/DL techniques to solve complex QA challenges across NVIDIA product lines, implementing DL-based solutions for video/audio defect detection and optimizing automated test frameworks to boost productivity. - Develop End-to-End GPU Validation Solutions: Create and maintain robust, Python-based automation pipelines that consume neural networks to rigorously validate NVIDIA GPUs. - Establish Scalable Infrastructure & Deployment: Set up and manage scalable development environments using Linux, Docker, and TensorRT to train, validate, and deploy large-scale neural networks. - Curate Self-Improving Data Pipelines: Build, clean, and augment high-quality datasets to feed and enable continuous, self-improving training pipelines. What we need to see: - Master’s or PhD in AI/ML/CS (or equivalent) with at least 2 years of hands‑on ML engineering experience. - Extensive knowledge of PyTorch, TensorFlow/Keras, ONNX, and TensorRT. - Advanced Python proficiency with strong OOP, design, and problem-solving skills for large-scale applications, combined with familiarity and hands-on experience in Linux and Docker. - Solid understanding of OpenCV and state-of-the-art DL algorithms for image classification, object detection, tracking, and segmentation. - Well-versed in QA methodologies with a deep understanding of NVIDIA GPU technologies (e.g., RTX, DLSS). - Hands-on experience building agentic gameplay systems using LLM/VLM-based agents, GenAI, RAG, vLLM, and solving complex problems with AIGC; proficient with AI development tools (Codex, Cursor, MCP, CodeRabbit) for test automation and workflow acceleration. - Excellent written and verbal communication, strong initiative, self-motivation, and a commitment to high software quality standards. Ways to stand out from the crowd: - Knowledge of Transformer based LLM and AIGC, Imitation Learning, Model free/based RL, Hierarchical RL, Inverse RL, Meta-learning, Life-long learning. - Hands-on experience in solving complex problems using Deep learning Algorithms would be a plus. - Experience and medals in data science or computer vision competitions (e.g., Kaggle, CVPR workshop) will be a plus. - Demonstrated ability to rapidly understand game dynamics and decompose game scenarios into solvable DL problems that can be implemented end‑to‑end.
Principal Product Manager, Agentic Workflows - Aut...
We are looking for a Principal Manager to join NVIDIA’s Automotive Product Management team with a focus on agentic workflows for autonomous vehicle (AV) development . In this role, you will define, design, and drive the implementation of AI-agent-powered workflows that accelerate how our engineering teams build, test, and deploy AV software. You will work at the intersection of generative AI, autonomous driving, and developer tooling to create reusable agents, skills, and orchestrated workflows that developers across NVIDIA and our partners can adopt in their own pipelines. You will collaborate with forward-thinking engineers, researchers, and business leaders across NVIDIA to translate the latest AI capabilities into productized agentic solutions—packaging them so they are discoverable, composable, and ready for integration into real-world AV development environments. What You Will Be Doing: - Define the product vision, architecture, and roadmap for agentic workflows that support AV development—from data curation and labeling, to simulation, training, validation, and deployment - Partner with engineering teams to design and implement end-to-end agentic workflows, specifying the agents, skills, tools, and orchestration logic required at each stage - Own the packaging and productization of agents, skills, and workflows so that internal and external developers can discover, configure, and integrate them into their own AV development pipelines - Synthesize requirements from AV engineering teams, customers, government regulations, and competitive benchmarking to prioritize the highest-impact workflow capabilities - Drive execution across teams (SW, HW, Safety, Operations, Integration) through technical engagements including architecture reviews, metric tracking, and sprint-level planning - Define use cases, acceptance criteria, and success metrics for each agentic workflow; ensure system design, safety, and quality are aligned with product goals - Own stakeholder alignment and negotiate feature roadmaps and prioritization with internal teams and external customers - Ensure development proceeds on schedule; proactively identify risks, resolve blockers, and maintain a program risk register - Support customer engagements and pre-sales discussions to demonstrate agentic workflow capabilities and align on deployment plans - Develop and promote standards, tools, templates, and documentation that enable developer self-service adoption of agentic workflows What We Need to See: - Strong understanding of ML/AI principles and technologies, with particular depth in large language models (LLMs), generative AI, and agentic AI frameworks (e.g., multi-agent orchestration, tool use, retrieval-augmented generation) - BS/MS (or equivalent experience) in Engineering, Computer Science, or a related field and 15+ years of product management experience spanning both software and hardware platformsDemonstrated experience defining and shipping AI-powered developer tools, platforms, or workflow automation products - Experience with autonomous vehicle development pipelines or ADAS—including data management, simulation, training, and deployment—is strongly preferred - Familiarity with on-device or edge computing as it relates to deploying AI models in automotive systems - Self-starter with a ‘can-do’ attitude who thrives in a fast-paced, multifaceted environment - Experience working in agile software development environments with modern product requirements and project management tools - Proven track record of leading the launch of technically complex products to customers - Strong technical leadership and communication skills, with the ability to drive alignment across large organizations and with customers Ways to Stand Out from the Crowd: - Hands-on experience with NVIDIA’s technology stack, including CUDA, TensorRT, Omniverse, Cosmos, Isaac, DRIVE, NIMs, or NeMo - Experience building agentic AI systems from concept to production—including agent design, skill libraries, workflow orchestration, and developer-facing APIs - Demonstrated experience with OpenClaw, NemoClaw, Hermes, LangChain - Experience deploying AI solutions in regulated or safety-critical production environments 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 July 24, 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 Perception Engineer, Obstacle Foundation Mo...
Intelligent machines powered by artificial intelligence—computers that can learn, reason, and interact with people—are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence, acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We are seeking an exceptional Senior Perception Engineer to help design and productize NVIDIA’s next-generation autonomous driving perception stack. You will work on the core 3D obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, multi-modal, and vision-language techniques where they add real value. What you’ll be doing: - Develop and improve the technical design, architecture, and roadmap for 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art CNN and transformer-based architectures where appropriate. - Design and implement advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion (camera, radar, lidar) for obstacle detection and tracking, including opportunities to explore BEV and transformer-based 3D perception. - Build efficient, production-grade deep learning models: define objectives with the team, select and prototype architectures, run experiments, and follow best practices for training and evaluation, using techniques such as large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA). - Help define and maintain KPI frameworks to quantify perception performance; analyze large-scale real and synthetic datasets to identify failure modes and systematically improve accuracy, robustness, and efficiency, incorporating approaches like self-supervised and representation learning when beneficial. - Contribute to the data strategy for perception: specify data and labeling requirements, help prioritize data collection and annotation, and collaborate with data and ground-truth teams, including model-assisted workflows (e.g., active learning, auto-labeling, vision-language models (VLMs)) and model-in-the-loop tooling. - Collaborate with safety, systems, and software teams to ensure perception solutions meet product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale. What we need to see: - PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. - Hands-on experience developing deep learning–based perception or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production. - Proven experience in data-driven development, including close collaboration with data, labeling, and ground-truth teams on data strategy, labeling quality, and iterative model improvement. - Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software. - Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams. Ways to stand out from the crowd: - Experience designing and deploying perception solutions for autonomous driving or robotics using camera-based deep learning at scale. - Hands-on experience architecting and deploying DNN-based perception pipelines on embedded or real-time platforms, including optimization for latency, memory, and compute constraints, and experience with modern architectures such as CNNs and transformers, plus familiarity with techniques like large-scale pretraining, parameter-efficient fine-tuning (e.g., LoRA), or vision-language models (VLMs). - Strong publication record or recognized contributions in deep learning, computer vision, or autonomous systems at leading conferences/journals (e.g., CVPR, ICCV, NeurIPS, IROS). - Deep understanding of 3D computer vision fundamentals, including camera modeling and calibration (intrinsic and extrinsic), multi-view geometry, and 3D representations, ideally with experience applying these concepts in transformer-based 3D or BEV perception pipelines. - Experience with CUDA development and optimizing training or inference pipelines through custom CUDA kernels or other GPU-accelerated components. 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 July 24, 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 Network Engineer - DGX Cloud
NVIDIA is looking for a Senior Network Engineer to develop a cloud network infrastructure. The goal is to craft a reliable, scalable and efficient network to support NVIDIA software development workflows and tools, including CI/CD pipelines, compute resource management flow and developer productivity tools. The network is serving the needs across the whole software stack for NVIDIA from Graphics Drivers to Autonomous Vehicles to Deep Learning frameworks. To achieve this goal, we are looking for an engineer who has a deep understanding of L3 underlay networks, outstanding design skills and a track record in building and delivering large-scale networks. What You Will Be Doing: - Lead the overall architecture and design of our cloud network infrastructure including intra-DC, inter-DC, Corp IT, and Internet connectivity - Implement, manage and troubleshoot entire network stacks. - Automate network infrastructure end-to-end including provisioning, management and monitoring. What We Need To See: - Expert knowledge in large scale IP Networking Technologies and protocols such as: MP-BGP, OSPF, ISIS, VRF, VxLAN, EVPN, QoS, GRE, IPSEC, DNS, MACsec. - Hands-on experience around Peering and Datacenter interconnect technologies: PNI, Transit, Exchange, Passive DWDM, Wave circuits. - Ability to write and understand Python/Shell scripts and programs for automation, tools, frameworks, dashboards, alarms. - Understanding of network virtualization such as: VRFs, VXLAN. Familiarity with Arista, Cumulus OS, Fortinet OS etc. Expert in the field of network, especially in underlay network. - Strong track record of implementing network services in a variety of distributed computing environments. - You have architected, built, and deployed a network for a large scale (1000s of machines) in the past, used by 1000s of people. Familiar with designing and building POPs and large scale WANs. - Hands-on experience with high performance network and network optimization in highly-available, large-scale, multisite, international environments. Great communication and presentation skills. - 8+ years of experience in network, especially experience in Arista switches. - BS Degree or the equivalent experience. Ways To Stand Out From The Crowd: - Hands-on background with building tooling and automation for provisioning, monitoring, and managing the network infrastructure. - Hands-on experience in designing and implementing networks at scale, such as automated deployments (e.g., ZTP) - Passionate about innovating and investing in ground breaking technologies. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. 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 208,000 USD - 333,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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 Customer Technical Program Manager - AI Dat...
We're looking for a Senior Customer Program Manager to lead the charge on technical programs for some of NVIDIA's most strategic partners to build exceptional customer relationship. As a core member of the Customer Program Management team, you'll work with the world's largest cloud service providers, hyperscalers, and their OEM/ODM partners to bring AI infrastructure to life at unprecedented scale. This role lives at the exciting intersection of engineering, operations, and customer engagement. We're looking for someone who brings deep technical program management skills, a strong engineering background, and a love for fast-paced environments where success comes down to tight alignment, sharp judgment, and great partnership. What you'll be doing: - Define program schedules, deliverables, and key milestones, keeping them tightly aligned with customer and partner requirements. - Translate customer requirements into clear, actionable plans across engineering, quality, logistics, and sales. And drive issues to resolution before they become roadblocks. - Lead horizontally across cross-functional teams, navigating high-priority critical issues and rallying globally dispersed teams around a shared set of objectives. - Serve as the face of NVIDIA to the customer, leading program kick-offs, technical deep dives, design reviews, issue and bug tracking, qualification and validation efforts, and status updates throughout the product lifecycle. - Drive program execution from early design through production deployment, ensuring timely delivery, exceptional quality, and customer acceptance. - Champion post-deployment sustaining support, acting as case manager for the issues that matter most. - Monitor factory production schedules, yields, and blockers, partnering closely with ODMs and contract manufacturers to crush issues and hit operational targets. - Communicate program health, risks, and key issues proactively to customers, internal partners, and leadership across Hardware, Software, Operations, Business, Quality, Sales, and Product teams—keeping everyone aligned while moving at full speed. What we need to see: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience. - 8+ years of program or project management experience in the IT industry. - Strong technical background in hardware and/or software engineering, with experience working closely with hyperscalers and their OEM/ODMs on AI factory build-outs. - A proven track record of leading complex, global programs from concept through deployment and production. - Outstanding program management, communication, and organizational skills, prioritizing the right issues and driving cross-functional alignment. - Demonstrated ability to coordinate across global teams and navigate multi-cultural, multinational business environments with ease. - Excellent interpersonal skills, with a talent for distilling complex technical concepts for any audience, from engineers to executives. - Willingness to travel as required (up to 5%) and a love for fast-paced, dynamic environments. Ways to stand out from the crowd: - Track record running end-to-end hardware and software product development and datacenter deployment. - Prior experience with deploying accelerated computing platform at-scale - Strong leadership in matrixed collaboration, conflict resolution, and consensus-building. - Proven expertise managing production schedules, optimizing line yields, and resolving complex field quality challenges. - Demonstrated success in dynamic, high-growth environments, with proven adaptability to ambiguity, rapid change, and matrixed team structures. 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 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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.
Engineering Manager - OpenBMC Platform
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. We are looking for an excellent engineering manager to own and deliver an end to end manageability stack for Data Center Systems. We are seeking an experienced manager who is deeply technical, hands-on, and has a wide system view. You will manage a team of experts, design & build OpenBMC based manageability software stack for NVIDIA’s next generation Data Center Compute Systems. We want to grow our teams with the smartest people in the world. If you're creative and autonomous, we want to hear from you! What you’ll be doing: - Own and deliver OpenBMC based manageability stack for next generation Data Center Compute Systems. - Own firmware delivered to data centers in terms of quality, reliability and telemetry performance. - Manage and lead a distributed team of software engineers to deliver firmware stack with high quality. - Work with data center architects and cloud customers for correct requirements and scope implementation to ensure speed of light product development. - Work closely with cross functional teams to ensure scalable manageability architecture for all data centers products - Drive efficiency, reliability and optimization in firmware architecture from a data center view point. - Work closely with customers and internal teams to resolve issues at Speed of Light. What we need to see: - BS, MS, or PhD in EE/CS or related field of education or equivalent experience. - 10+ overall years of relevant experience working on server firmware (BMC) and platform software development - 5+ years of experience in managing a software/firmware engineering team - Hands on experience with data center health management workflow. Proven record of delivering server firmware for large data centers. - Strong knowledge of data center management, server architecture and server manageability in data centers. - Strong and demonstrable skill in C/C++ and Python. Experience programming and debugging skills for server platforms. - Experience in SCM (e.g. Git, Perforce) and project management tools like Jira. - Possess excellent written and oral communication skills, good work ethics, high sense of team-work, love to produce quality work. Self-starter who loves to find creative solutions to complicated problems Ways to stand out from the crowd: - Hands on experience with BMC firmware/software stack for data center health management and server manageability. - Proven engineering managers driving large complex problem with 25+ engineers working 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! 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 3, and 272,000 USD - 431,250 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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.
Deep Learning Software Engineer, TensorRT Performa...
We are now looking for a Deep Learning Software Engineer, TensorRT Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of NVIDIA’s inference ecosystem! NVIDIA is rapidly growing our research and development for Deep Learning Inference and is seeking excellent Software Engineers at all levels of expertise to join our team. Companies around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in areas like Generative AI, Recommenders and Vision that have put DL into every software solution. Join the team that builds the software to enable the performance optimization, deployment and serving of these DL inference solutions. We specialize in developing GPU-accelerated deep learning inference software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models. Collaborate with the deep learning community to integrate TensorRT into OSS frameworks like TensorRT-EdgeLLM and PyTorch. Identify performance opportunities and optimize SoTA models across the spectrum of NVIDIA accelerators, from datacenter GPUs to edge SoCs. Implement graph compiler algorithms, frontend operators and code generators across NVIDIA’s inference ecosystem. Work and collaborate with a diverse set of teams involving workflow improvements, performance modeling, performance analysis, kernel development and inference software development. What you'll be doing: - Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA’s inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT) - Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT. - Develop new model pipelines for NVIDIA’s inference ecosystem with optimized performance including but not limited to areas like quantization, scheduling, memory management, and distributed inference to set the gold standard for Gen AI performance. - Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to set directions and develop innovative inference solutions. - Scale performance of deep learning models across different architectures and types of NVIDIA accelerators. What we need to see: - Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Science, Computer Engineering, EECS, AI). - 2 years of relevant software development experience. - Strong C++, Python programming and software engineering skills - Experience with DL frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX) and inference libraries (e.g. TensorRT, TensorRT-LLM, vLLM, SGLang, FlashInfer). - Experience with performance analysis and performance optimization Ways to stand out from the crowd: - Strong foundation and architectural knowledge of GPUs. - Deep understanding of modern deep learning models and workloads (e.g. Transformers, Recommenders, ASR, TTS, Visual Understanding). - Proficiency in one of the deep learning programming domain specific languages (e.g. CUDA/TileIR/CuTeDSL/cutlass/Triton). - Prior contributions to major LLM inference frameworks (e.g. vLLM) or prior experience with graph compilers in deep learning inference (e.g. TorchDynamo/TorchInductor). - Prior experience optimizing performance for low-latency, resource-constrained systems or embedded AI pipelines (e.g. Jetson systems or other edge AI accelerators). GPU deep learning has provided the foundation for machines to learn, perceive, reason and solve problems posed using human language. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as “the AI computing company.” Come, join our DL Architecture team, where you can help build a real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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 Platform Telemetry Engineer
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We are looking to grow our company and establish teams with the most thoughtful people in the world. NVIDIA GH200 superchip provides performance and productivity required for strong scaling for HPC and generative AI workload. Scale out is inherent to the design of this massive superchip. We are looking for expert engineers to come and help design rack level solutions for next generation scaling AI supercomputing platforms. Join us at the forefront of technological advancement. What you will be doing: - Drive next generation fleet management solutions for scaling AI infrastructure using GPUs and Grace solution from Nvidia. Work with customers, product management and other architects to narrow down on requirements for implementation to ensure speed of light product development. - Bring up clarity on architecture for fleet health monitoring and fault-remediation solution at scale. Work with customers and other architects, understand their requirements on health monitoring, making best use of available capabilities in-band as well as out of band. Detailed architecture, do POCs to validate architecture. - Educate customers about product architecture and take feedback to make necessary changes. Write architecture specs, design documents and own end to end delivery of product by working across the teams. Do code review for the code produced because of architecture specs. - Ensure product is properly tested by working with the development team to enhance unit testing and proper test plan in place. - Drive product life cycles with QA teams to productize the code and be responsible as a product owner. - Articulate requirements as part of Jira and bug management tools and work out an end-to-end execution plan in collaboration with other managers. - Contribute to all phases of product development, from product definition, architecture, and design, through implementation, debugging, testing and early customer support. What we need to see: - BS, MS, or PhD in EE/CS or related field of education (or equivalent experience). - 5+ years hands-on coding experience - Strong knowledge of time series databases like Influxdb & Prometheus. Strong knowledge of building and consuming REST APIs (Redfish is big plus). Strong knowledge of telemetry visualization solutions like Grafana & Influx. Strong knowledge of firmware architecture, optimize firmware for low latency APIs. Strong knowledge of analyzing algorithms for time & space complexity and project system resource requirements. - Proven record of solutions for scalability - Strong and demonstrable skill in C/C++ and Python - Experience programming and debugging skills for server platforms. - Experience in SCM (e.g., Git, Perforce) and project management tools like Jira. - You should possess excellent written and oral communication skills, excellent work ethics, a great sense of teamwork, 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 complicated problems and hands on with coding. Ways to stand out from the crowd: - Experience building telemetry collection & analysis engines. Experience with Redfish. Experience with notification systems like PagerDuty. - Active Open Compute (OCP) and DMTF contributor in relevant areas. Hands on with x86 or ARM system architecture. - Familiarity with Confidential Compute. - Experience with ML and multi-variable optimization techniques. NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you! 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 July 24, 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 Software Engineer, AI Storage
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most inquisitive people in the world. Join us at the forefront of technological advancement. What you’ll be doing: - Work on first solutions in the industry that bring exceptional performance and security improvements to the infrastructure used by leading applications. - Develop new features and enable various technologies around data storage for GPU IO. - Develop advanced C++/CUDA libraries and algorithms for speed-of-light performance - Remove performance bottlenecks by coming up with optimization(s) in the IO stack, frameworks, and applications. - Work collaboratively with other specialists including the research teams and be willing to take on complex engineering tasks that progress towards the goals of the team and the company. What we need to see: - Good knowledge of Linux kernel internals, Filesystem, Object storage systems, Databases, Vector Databases - Good understanding of NVMe and related technologies - Development experience in Cloud, Virtualization (VMware, KVM), Container technologies. - Advanced knowledge in Computer Architecture - Solid understanding in data structures and algorithms - Bash and Python experience - Excellent communication and planning skills. - BS or MS or PhD in computer science or a related field or equivalent experience. - 7+ years of strong coding experience using C, C++, Rust, Python Ways to stand out from the crowd: - Development experience in storage software such as Key-Value, File systems object storage systems, Vector Databases - Internals of frameworks like PyTorch, JAX - Exceptional CUDA programming skills. Exceptional C++ programming 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 dedicated people on the planet 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 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 July 24, 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.
Performance Engineer, Deep Learning and HPC
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. Our team is responsible for generating benchmark data across a rapidly growing catalog of Deep Learning & HPC frameworks/applications on Nvidia and as well as competitive products. The data that we collect drives marketing/sales collaterals as well as engineering studies for current and future products. In some instances, we’ll write scripts that improve the team’s ability to gather data through automation and designing efficient processes for testing a wide variety of applications and hardware. You will have the opportunity to work with multi-functional teams and in a dynamic environment where multiple projects will be active at once and priorities may shift frequently. We are now looking for a Performance Engineer focused on Deep Learning (DL) & High-Performance Computing (HPC) applications to join our diverse team. What you'll be doing: - Plan and execute performance benchmarking across a wide range of HPC and DL frameworks and applications - Aggregate, analyze, and generate written and visual reports with the testing data for internal sales, marketing, SW, and HW teams - Develop Python scripts to automate the testing of DL & HPC-focused applications - Work with internal engineering team to debug performance issues - Learn to use the latest applications in the areas of advanced machine learning and HPC - Assist with the development of tools and processes that improve our ability to perform automated testing What we need to see: - B.S. in Computer Engineering, Computer Science or related technical field (or equivalent experience) - 2+ years of experience - Excellent programming and debugging skills in a scripting language such as Python or Unix shell - Advanced knowledge using Linux based systems (Ubuntu and CentOS strongly preferred) - Proficient in compiling software from source code, including debugging errors encountered - Excellent English verbal and written interpersonal skills to improve collaboration with coworkers - Excellent data analysis skills and the ability to summarize findings in a written report - Familiarity using a container platform such as Docker or Singularity Ways to stand out from the crowd: - Experience using a GPU-enabled deep learning framework such as PyTorch, MXNet, or TensorRT - Experience using GPU-enabled HPC applications such as LAMPS, GROMACS, Amber, RTM, etc… - GPU/CPU benchmarking on cloud solutions from AWS, GCP, Azure - Software compilers such as GNU, Intel Composer, or PGI - Previous experience with computer clusters and cluster orchestration and scheduling tools. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 212,750 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 24, 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 Deep Learning Framework Communications Engi...
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: - Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production - Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. - Improve AI compilers to hide communications or perform automatic fusion. - Conduct in-depth AI workload performance characterization on multi-GPU clusters. - Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. - Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms. - Influence the roadmap of communication libraries - NCCL & NVSHMEM. - Collaborate with a very dynamic team across multiple time zones. What we need to see: - B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience - Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang - Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) - Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) - Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) - Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) - Adaptability and passion to learn new areas and tools - Flexibility to work and communicate effectively across different teams and timezones Ways to stand out from the crowd: - Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) - Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes - Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout 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 July 24, 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 System Software Engineer – Dynamo Tools
We are seeking a Senior System Software Engineer to own and advance the AI-Perf analysis, NVIDIA’s flagship framework for benchmarking, experimentation, and analysis of LLMs, Generative AI, and deep learning inference workloads. In this role, you’ll combine systems research, distributed systems engineering, and applied AI, enabling reproducible performance evaluation, influencing internal platforms, and providing tooling that empowers researchers and engineers globally. What you’ll be doing: - Lead the design, development, and roadmap of AI-Perf, defining benchmarking methodologies, performance metrics, and reproducible experimental workflows. - Build scalable and high-performance features to measure latency, throughput, and efficiency across AI models and distributed systems. - Partner with AI researchers, platform teams, and engineers to translate experimental challenges into robust, user-friendly performance tooling. - Integrate AI-Perf with the Dynamo Inference Stack, other NVIDIA inference stacks, and open-source inference frameworks, delivering end-to-end performance insights for researchers and production users. What we need to see: - Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or related field—or equivalent experience. - 3+ years of experience in systems software, distributed performance engineering, or AI infrastructure research. - Expert-level Python skills, including profiling, optimization, automation, and debugging of complex systems. - Deep knowledge of distributed systems concepts, including scalability, concurrency, fault tolerance, and performance trade-offs. Ways to stand out from the crowd: - Experience designing or maintaining performance benchmarking frameworks or tooling for AI/ML systems. - Hands-on experience with LLMs and deep learning frameworks such as PyTorch, TensorFlow, TensorRT, or ONNX Runtime. - Contributions to open-source or research projects in AI performance, infrastructure, or distributed systems. - Experience running large-scale inference experiments across cloud and on-prem environments (AWS, Azure, GCP, bare metal). Why you’ll love this role - Impact at scale: Your work will define how AI performance is measured, optimized, and understood by engineers and researchers worldwide. - Innovation and ownership: Lead a critical tool used by internal teams and external partners, shaping the AI benchmarking ecosystem. - Collaborative research environment: Work closely with world-class AI researchers, engineers, and platform architects on cutting-edge inference challenges. - Visibility and growth: Contribute to tooling that powers publications, benchmarks, and industry-leading AI performance insights. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you! 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 July 24, 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 Robotics Research Scientist
We are now looking for a Senior Robotics Research Scientist! NVIDIA is at the forefront of the AI and robotics revolution, and our robotics teams are on a mission to build the essential technology that can enable any company to become a robotics company. The Seattle Robotics Lab is focused on fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, and simulation. This research aims to transform research paradigms, transfer into NVIDIA’s robotics and simulation products, and create new robotics markets for the world. The Seattle Robotics Lab has led many influential works that have been presented at top robotics, AI, and computer vision conferences; these works include BayesSim , cuRobo , DeXtreme , DiSECT , Factory , GraspNet , ITPS , MimicGen , RVT , and SHAC . (See our publications page for a complete list.) The work has deeply impacted the research community and NVIDIA products, including Isaac Sim , Isaac Lab , and Isaac Manipulator . Furthermore, SRL collaborates closely with other research and engineering teams to advance and leverage the Cosmos and GR00T-N foundation models, as well as the Newton physics simulation engine. The team is targeting several grand challenges in robotics and is aiming to achieve never-before-seen capabilities within 2-3 years. We are looking for world-class senior research scientists to play a pivotal role in these efforts, providing both technical leadership and hands-on technical contributions. These scientists must have exceptional research and engineering skills, a proven research track record, strong supporting references, and a team-first mentality. What you will be doing: - Developing algorithms, models, and methods for robotic manipulation and loco-manipulation, for both industrial and household applications; - Integrating these methods into real-world robotic manipulation systems, including those consisting of collaborative robot arms, industrial robot arms, mobile manipulators, humanoids, and dexterous hands; - Co-leading and contributing to multi-person research projects that require a diverse set of skills across the robotics and machine learning stack; - Engaging with the academic community through high-impact publications, conferences, workshops, and code releases; - Collaborating with product managers and engineering teams to transfer your research into NVIDIA products that will have real-world impact; - Mentoring interns and more junior research scientists and engineers. What we need to see: - A PhD in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field (or equivalent experience). At least 3 years of research experience after completing your PhD; 5+ years is preferred. - Deep knowledge of both the theory and practice of robotics and AI, with a strong interest in connecting your work to real-world robotics applications. - A proven track record of research excellence, with work published in top robotics and AI conferences and journals such as RSS, CoRL, ICRA, IROS, IJRR, T-RO, NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, and EMNLP. - Exceptional communication, collaboration, and interpersonal skills, with significant experience working on teams as both a leader and a contributor. - Exceptional programming skills in Python; in addition, familiarity with C++, CUDA, and Warp is a plus. - Fluency in modern deep learning frameworks such as PyTorch and JAX. Significant experience with robotics frameworks such as ROS2 and physics simulation frameworks such as Isaac Sim, Isaac Lab, and MuJoCo. - Deep comfort in working through the complexities of simulation and real-world robotics, including debugging physics simulators and renderers under rapid development; selecting, setting up, maintaining, and enhancing complex robotics hardware; debugging communication systems; and designing robust workflows for model training and evaluation. Ways to stand out from the crowd: - Prior experience working with product managers and engineering teams to transfer research into products is a significant plus. - A history of successfully mentoring junior researchers, engineers, and/or interns. - Experience with one or more of the following research areas and applications, which are of particular interest: - Bimanual and dexterous manipulation - Mobile manipulation and humanoid loco-manipulation - Multisensory perception (e.g., vision, tactile, and force/torque sensing) - Simulation, sim-to-real, and real-to-sim - Vision-language-action (VLA) models, including architectural advancements, large-scale training, and test-time reasoning - Industrial applications, such as bin-picking, kitting, and assembly The Seattle Robotics Lab is now located in a brand-new office in the vibrant Fremont neighborhood of Seattle. Widely considered to be one of the technology world’s most desirable employers, NVIDIA has some of the most forward-thinking and hardworking people in the world inventing the future for us. Are you a creative and collaborative researcher interested in seeking new challenges? If so, we want to hear from you! Please join us and be at the forefront of robotics research that will impact both industry and academia! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 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 July 24, 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.
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