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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology—and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking a highly motivated and experienced SAP master data (MM/PP) within the Enterprise Data Management Team. You will serve as the strategic link between business processes and technical data architecture. You will be responsible for the integrity, governance, and optimization of critical supply chain and production data objects. This role requires a deep functional understanding of Materials Management (MM) and Production Planning (PP), specifically tailored to the complexities of the semiconductor industry. What You’ll Be Doing: Enterprise Data Architecture: Lead the functional design and governance for critical supply chain data domains, including but not limited to Material Master, BOM, ECN (Engineering Change Management), Routing, Production Versions (PV). PLM Integration: Manage the seamless end-to-end integration between SAP PLM and core ERP (MM/PP), ensuring engineering designs transition accurately into manufacturing master data. Develop a deep understanding of the end-to-end chip supply chain, including chip family and part creation, PLM system input/output/yield linkage, ECC material master setup and extension and the ontology/knowledge graph foundation supporting EDM’s agentic AI initiatives. Process Automation: Design and implement custom workflows and automated solutions for the "Part Creation" lifecycle to reduce manual entry and accelerate time-to-market. Integrated Supply & Demand Planning: Partner with business leaders to align Supply & Demand Planning requirements with master data support, ensuring that data structures are optimized for advanced planning systems such as SAP IBP, APO, and Anaplan. Custom Object Support: Strong experience in defining and supporting custom SAP objects tailored to specific complex manufacturing or supply chain business requirements. Collaborate with different IT and business teams to translate complex supply chain and semiconductor requirements into scalable, governed, and business-aligned data solutions. Support master data setup and enhancement requirements arising from business process changes and IT transformation initiatives; contribute to data migration and validation for ECC-to-S/4HANA transitions; and serve as the cross-functional liaison across business, data, and technology teams. What We Need to See: 8+ years of SAP experience with Core focus on the SAP Production Planning, Manufacturing, Material Management, and integration Knowledge with PLM systems. Deep understanding of maintenance and governance of complex & high-volume master data objects like Materials, BOMs, Routings, PV, and ECNs. At-least 1 SAP S/4 HANA implementation experience in Materials Management, Production Planning and Manufacturing. Familiarity with SAP Fiori/UI5 interfaces used in S/4 HANA for master data maintenance apps. Proficiency in writing functional specifications and working with ABAP developers Hands-on experience developing custom enhancements (User Exits, BAdIs) and workflow logic to trigger automatic data validation and creation. Handle third-party system integrations with SAP using IDocs, BAPIs, and Interfaces. (Optional/Good-to-have) Use debugging skills to trace issues and collaborate with technical teams. Experience with data governance tools like SAP MDG/ Informatica (Preferred) Education: Bachelor’s or master’s degree in Computer Science, Information Systems, Data Engineering, Industrial Engineering, or equivalent experience in enterprise data architecture and data platform implementations. Familiarity with AI-enabled productivity and data platforms such as ChatGPT, Copilot, Gemini, or Claude to improve automation, data quality, and decision-making. NVIDIA is recognized as one of the technology world’s most sought-after employers. Our workforce includes some of the most innovative and dedicated individuals globally. If you're imaginative, driven to reach objectives, and enjoy a lively work environment, then why wait? Apply today! Known as one of the most attractive employers in the tech industry, NVIDIA offers attractive salaries and an extensive benefits package. When planning your future, explore the opportunities accessible to both you and those close to you at www.nvidiabenefits.com/

We are looking for a talented Senior System Software Engineer to help build NVIDIA Halos, our full-stack safety platform for physical AI: autonomous vehicles, humanoids, industrial robots, and intelligent machines that sense, decide, and act in the real world. This role sits at the intersection of embedded systems, rich operating systems, safety, security, virtualization, and accelerated computing. If you have a good understanding of System Software development on Real Time OS (RTOS), ARM architecture, Virtualization, strong C and/or Ada/SPARK programming skills, and experience with formal methods, we want to hear from you! We are a leading artificial intelligence computing company and are paving the way with innovations in gaming, visualization, supercomputing, and autonomous vehicle and robotics safety platforms. NVIDIA gives automakers, tier-1 suppliers, automotive research institutions, and startups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for autonomous vehicles. Our unified computing architecture makes it possible to train deep neural networks in the data center on the NVIDIA DGX™, and then seamlessly run them on NVIDIA's Halos platform inside the vehicle. Leading vehicle manufacturers, tier 1 suppliers, mapping and simulation companies, software and sensor providers, and startups around the world are developing on the NVIDIA Halos® platform to deliver the best solutions for the new world of mobility. As a System Software Engineer, you will get an opportunity to work on high-performance NVIDIA edge AI platforms running complex mixed-criticality software stacks across QNX, Linux, hypervisors, safety partitions, accelerators, and real-time AI workloads, and work alongside industry experts in diverse teams and projects. What you’ll be doing: Design, develop and debug system software for NVIDIA Halos OS across QNX, Linux, and hypervisor-based environments. Design and develop BSP, boot, driver, device-management, diagnostics, and platform software for NVIDIA SoCs and edge AI platforms. Design & develop I/O Virtualization solutions for mixed-criticality systems Develop safe and secure software compliant with ISO 26262 and ISO 21434 standards. Bring up and optimize next-generation NVIDIA platforms, working closely with ASIC, firmware, OS, safety, security, and platform teams. Use Formal Methods to architect and develop high integrity software Use GenAI and AI-assisted engineering tools to accelerate debugging, test development, code review, documentation, requirements analysis, and workflow automation. Design debugging, tracing, logging, and performance-analysis solutions that improve developer experience Handle complex issues requiring interactions between components partitioned across the large software stack Mentor junior engineers What we need to see: Bachelors/Masters or equivalent experience in Computer Science 5+ years of experience in System Software architecture and development for real time embedded systems Strong understanding of computer architecture and operating system fundamentals Experience in designing and developing solutions for complex system problems. Strong C and/or Ada/SPARK programming and debugging skills Practical experience using AI-assisted development tools for coding, debugging, testing, documentation, or workflow automation. Hands-on experience with debugging tools, performance analysis and system analyzer tools A dedicated, team and results oriented, self-motivated contributor with excellent analytical and interpersonal skills Ways to stand out from the crowd: In-depth knowledge of embedded systems and real time operating systems, like QNX and RT Linux skills Good understanding of ARM architecture and low level software development for ARM v8 based SOCs Prior hands-on experience in Ada/SPARK programming (including specification and formal verification) and TLA+ formal verification modeling Experience performing architectural safety analysis (FMEA/DFA) and security analysis (Threat modeling) Background in software development in compliance to ISO 26262 standard 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/ We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We are looking for a talented Senior System Software Engineer to help build NVIDIA Halos, our full-stack safety critical platform for physical AI: autonomous vehicles, humanoids, industrial robots, and intelligent machines that sense, decide, and act in the real world. This role is equally grounded in ISO 26262 functional safety engineering and embedded systems, rich operating systems, virtualization, accelerated computing. If you have a good understanding of System Software development on Real Time OS (RTOS), ARM architecture, Virtualization, and experience with ISO 26262 safety lifecycle, we want to hear from you! We are a leading artificial intelligence computing company and are paving the way with innovations in gaming, visualization, supercomputing, and autonomous vehicle and robotics safety platforms. NVIDIA gives automakers, tier-1 suppliers, automotive research institutions, and startups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for autonomous vehicles. Our unified computing architecture makes it possible to train deep neural networks in the data center on the NVIDIA DGX™, and then seamlessly run them on NVIDIA's Halos platform inside the vehicle. Leading vehicle manufacturers, tier 1 suppliers, mapping and simulation companies, software and sensor providers, and startups around the world are developing on the NVIDIA Halos® platform to deliver the best solutions for the new world of mobility. As a System Software Engineer, you will get an opportunity to work on high-performance NVIDIA edge AI platforms running complex mixed-criticality software stacks across QNX, Linux, hypervisors, safety partitions, accelerators, and real-time AI workloads, and work alongside industry experts in diverse teams and projects. What you’ll be doing: Own and drive the ISO 26262 functional safety lifecycle for NVIDIA Halos platform components from safety plan to safety analysis for mixed-criticality software stacks. Architect, design and develop system software for NVIDIA Halos OS across QNX, Linux, and hypervisor-based environments. Use GenAI and AI-assisted engineering tools to accelerate debugging, test development, code review, documentation, requirements analysis, and workflow automation. Handle complex issues requiring interactions between components partitioned across the large software stack Mentor junior engineers What we need to see: Bachelors/Masters or equivalent experience in Computer Science 8+ years of experience in System Software architecture and development for real time embedded systems 4+ years of direct, hands-on ISO 26262 functional safety engineering experience. Strong understanding of computer architecture and operating system fundamentals Experience in designing and developing solutions for complex system problems. Practical experience using AI-assisted software development lifecycle. A dedicated, team and results oriented, self-motivated contributor with excellent analytical and interpersonal skills Ways to stand out from the crowd: Demonstrated experience owning ISO 26262 safety lifecycle activities: FMEA/DFA, CPA, safety case development, and working with independent assessors. In-depth knowledge of embedded systems and real time operating systems, like QNX and RT Linux Good understanding of ARM architecture and low level software development for ARM v8 based SOCs Prior hands-on experience in Ada/SPARK programming (including specification and formal verification) and TLA+ formal verification modeling 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/ We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

By submitting your resume, you’re expressing interest in our 2027 RDSS (Research and Development Substitute Services) program. Please confirm your eligibility with the local district office before applying the role. NVIDIA is seeking phenomenal engineers to improve our verification methodology, so we can validate the world’s largest design efficiently. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. We are now looking for a DFT Engineer in our Taiwan, Taipei/Hsinchu Office! What you’ll be doing: Develop in-house software to enable advanced testing on NVIDIA hardware. Create automation flows to support ATPG and DFT requirements. Optimize software performance and drive quality improvements. Collaborate closely with Design, DFT, and Test Engineering teams to ensure test quality, improve efficiency, and support silicon bring-up. What we need to see: Master’s degree in Electrical Engineering, Computer Engineering, or Computer Science. Strong programming skills in Python and C++ (required). Experience with TCL, Perl, Java, or other programming languages is a plus. Strong communication skills with the ability to work effectively in a team environment. Fluency in English (spoken and written). Ways to stand out from the crowd: Knowledge of Design for Testability (DFT) concepts, including Scan, ATPG, and JTAG.

We are seeking a passionate QA Engineer to join our FW testing team. This position will be part of our growing team, helping NVIDIA products meet industry-leading benchmarks for efficiency and quality. As a Firmware QA Engineer, you will be immersed in the latest advancements and actively contribute to developing world-class products. Your efforts will directly impact the performance and quality of our offerings, ensuring they consistently meet industry-leading standards. We are looking for ideal candidates who will actively test industry-leading features in the FW sector, quickly learn new features, conduct both manual and automated testing, and contribute to the development of automation systems. What you'll be doing: Review arch design and requirements documents for new features introduced in the Nvlink program Join the effort of QA shift left towards simulation for NVL7 generation Design, develop, and perform tests for the new features, as part of FW GA or update releases. Automate newly added tests in the existing automation framework, and add new capabilities and features to the framework. Report bugs found during execution, assist with reproduction and debugs to understand root cause, verify bug fixes provided by R&D team, and raise if not fixed. Fully collaborate with different external teams like : :product marketing, R&D, and verification. Define and build setups topologies for appropriate product coverage. What we need to see: Practical / BSc in Computer Science or Electrical/Electronics Engineering. 0-3 years of proven experience Clear verbal and written communication, proficient in written and spoken English. Self-reliant individual, capable of planning and carrying out tasks within their assigned area. Personal: good interpersonal skills, quick learner, proactive, innovative, highly motivated, and committed. Ways to stand out from the crowd: Scripting skills and proven experience in Python or other programming languages Proven experience in QA - methodologies, and test design. Working in a fast-paced environment with multiple parallel running activities. Knowledge/experience in Networking protocols. Knowledge of Linux/Windows OS. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

We are looking for a Software Engineering Manager to lead a team responsible for platform expansion & readiness, enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to the world’s AI infrastructure and must deliver functionality and performance on every target. In this role, you will lead and build a team that provides a single accountable organization for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will be hands-on engineers who also have experience leading software product engineering teams in accelerated computing domains. If this sounds exciting, we would love to meet you! What You’ll Be Doing: Lead, mentor, and develop your team. Own end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance. Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines. Perform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness, and referring to a library specialist as needed. Identify performance targets for new platforms, establish performance testing and fix performance regressions. Define and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms. Work closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations. What We Need to See: PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience). 8+ years of overall experience developing high-performance numerical software. 3+ years leading and mentoring software engineering teams. Hands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python. Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning. Strong communication, collaboration, and documentation habits. Experience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA. Ways to Stand Out from the Crowd: Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads). Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers). Proven track record using Agentic AI to boost your efficiency and code quality. Experience with cross-platform software development and platform bring-up across multiple architectures. Experience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262). #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 October 2, 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.

We are looking for a Software Engineering Manager to lead a team responsible for platform expansion & readiness, enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to the world’s AI infrastructure and must deliver functionality and performance on every target. In this role, you will lead and build a team that provides a single accountable organization for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will be hands-on engineers who also have experience leading software product engineering teams in accelerated computing domains. If this sounds exciting, we would love to meet you! What You’ll Be Doing: Lead, mentor, and develop your team. Own end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance. Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines. Perform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness, and referring to a library specialist as needed. Identify performance targets for new platforms, establish performance testing and fix performance regressions. Define and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms. Work closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations. What We Need to See: PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience). 8+ years of overall experience developing high-performance numerical software. 3+ years leading and mentoring software engineering teams. Hands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python. Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning. Strong communication, collaboration, and documentation habits. Experience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA. Ways to Stand Out from the Crowd: Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads). Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers). Proven track record using Agentic AI to boost your efficiency and code quality. Experience with cross-platform software development and platform bring-up across multiple architectures. Experience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262). #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 October 2, 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.

We are looking for a Software Engineering Manager to lead a team responsible for platform expansion & readiness, enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to the world’s AI infrastructure and must deliver functionality and performance on every target. In this role, you will lead and build a team that provides a single accountable organization for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will be hands-on engineers who also have experience leading software product engineering teams in accelerated computing domains. If this sounds exciting, we would love to meet you! What You’ll Be Doing: Lead, mentor, and develop your team. Own end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance. Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines. Perform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness, and referring to a library specialist as needed. Identify performance targets for new platforms, establish performance testing and fix performance regressions. Define and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms. Work closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations. What We Need to See: PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience). 8+ years of overall experience developing high-performance numerical software. 3+ years leading and mentoring software engineering teams. Hands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python. Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning. Strong communication, collaboration, and documentation habits. Experience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA. Ways to Stand Out from the Crowd: Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads). Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers). Proven track record using Agentic AI to boost your efficiency and code quality. Experience with cross-platform software development and platform bring-up across multiple architectures. Experience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262). #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 October 2, 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.