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NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. You will be responsible for the architecture, technical plan, and production results of a major platform area like ingestion and orchestration, data quality and reconciliation, or data serving and consumption. You will clarify requirements with customers, define technical objectives, guide design and development among engineers and partner teams, and stay actively engaged in coding, debugging, and production tasks. Successful candidates have already led complex technical work across team boundaries and delivered improvements that other groups adopted. Our primary implementation environment is Python, SQL, Databricks, and Spark. What you’ll be doing: You will own a major platform component and its roadmap. For example, define its architecture, interfaces, technical goals, and evolution. Anticipate capacity, compatibility, and operational needs over a multi-year horizon, and translate them into achievable breakthroughs that balance immediate delivery with long-term maintainability. Lead technical delivery across teams. Work with customers and interested parties to clarify vague requirements. Break down design and implementation work for contributing engineers. Establish release turning points and manage dependencies and delivery risks. Guide the work process, revise plans when requirements shift, and keep management and partner teams informed and aligned. Build data pipelines and products. Plan and carry out batch and streaming ingestion, transformation, reconciliation, and serving processes for fleet, capacity, utilization, cost, scheduling, and operational telemetry. Establish data models and agreements that remain stable as sources, consumers, and scale progress. Develop shared platform capabilities. Direct the creation and adoption of libraries, workflow and DAG or comparable experience abstractions, deployment tools, and standard implementation approaches. Partner with related teams to solve shared challenges and evaluate progress in onboarding time, engineering effort, reliability, and cost. Lead complex production investigations. Serve as the technical point of accountability for issues spanning pipelines, applications, SQL engines, Spark, storage, networks, and cloud services. Coordinate investigations across owners, drive resolution of release blockers and critical issues from partners, and implement preventive measures. Define quality, security, and operational expectations. Establish and implement testing, data-quality, reconciliation, lineage, SLO, and release-readiness standards for your platform area. Partner with security and infrastructure teams on trust boundaries, service identities, least privilege, secrets, environment isolation, and auditability, and drive adoption across contributing teams. Make trusted data usable. Deliver well-modeled tables, APIs, automation, dashboards, and focused internal applications. Align with consumers on semantics, access patterns, freshness, compatibility, and ownership so that shared capabilities support dependable operational decisions. Provide technical leadership through others. Guide design reviews, mentor engineers taking on larger ownership, and resolve technical disagreements using evidence and clear tradeoffs. Partner with leadership on priorities and explain how technical investments support DGXC objectives. What we need to see: BS or MS in Computer Science, Engineering, or a related field (or equivalent experience), and at least 12+ years of equivalent experience A sustained record of building and operating production software, data platforms, databases, or distributed systems. This includes owning a major component or complex project from requirements and architecture through release and ongoing operation. Proven ability to outline a component’s technical plan, establish objectives for engineers, assign design and implementation tasks, and guide delivery within your team and nearby teams with little supervision. Extensive practical experience in one or more of these areas: distributed processing using Spark or a similar system; relational, distributed, or analytical databases; production ETL, change-data capture, streaming, or event handling; or backend and cloud platforms managing large data volumes. You must grasp the interfaces and failure modes of nearby layers thoroughly to inform solid architectural choices. Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language, with the ability and willingness to work primarily in Python and SQL. Experience designing reusable abstractions, reviewing substantial changes, and personally implementing and debugging critical code paths. Strong SQL and data-modeling skills, with practical depth in query execution, incremental processing, schema evolution, consistency, and analytical consumption. Ability to reason about idempotency, replay, late-arriving data, partial failure, and correctness across system boundaries. Experience leading complex investigations involving multiple components and teams. Ability to use logs, metrics, traces, query plans, profiles, and controlled experiments to establish root cause, coordinate resolution, and prevent recurrence. Demonstrated architectural judgment: evaluating alternatives, anticipating future requirements, and balancing reliability, performance, cost, security, compatibility, and maintainability. Experience leading significant migrations or architectural changes while preserving production service. Experience establishing production quality and operational practices that other engineers adopt, including testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment. Proven success in influencing technical decisions without official authority, advising engineers outside your immediate project, and advancing workflow improvements across closely related teams. Ability to simplify complex issues, offer a course of action, and communicate decisions and delivery risks clearly. Ways to stand out from the crowd: Proven expertise in building, refining, and running Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, or Unity Catalog workloads along with shared platform features. Experience designing and operating Kafka or comparable streaming systems, including partitioning, consumer behavior, offset management, backpressure, replay, and schema compatibility. Experience scaling, migrating, or tuning relational, distributed, time-series, object-storage, or information retrieval systems, including Elasticsearch or OpenSearch. Background operating compute or GPU clusters, or working with Kubernetes, Slurm, cloud infrastructure, and fleet telemetry across AWS, Azure, GCP, or other providers. Experience building production agentic systems or agent harnesses, including tool integration, context management, evaluation, permissions, observability, and failure recovery. Evidence of measurable improvements in engineering productivity or operational outcomes. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 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.

NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. You will be responsible for the architecture, technical plan, and production results of a major platform area like ingestion and orchestration, data quality and reconciliation, or data serving and consumption. You will clarify requirements with customers, define technical objectives, guide design and development among engineers and partner teams, and stay actively engaged in coding, debugging, and production tasks. Successful candidates have already led complex technical work across team boundaries and delivered improvements that other groups adopted. Our primary implementation environment is Python, SQL, Databricks, and Spark. What you’ll be doing: You will own a major platform component and its roadmap. For example, define its architecture, interfaces, technical goals, and evolution. Anticipate capacity, compatibility, and operational needs over a multi-year horizon, and translate them into achievable breakthroughs that balance immediate delivery with long-term maintainability. Lead technical delivery across teams. Work with customers and interested parties to clarify vague requirements. Break down design and implementation work for contributing engineers. Establish release turning points and manage dependencies and delivery risks. Guide the work process, revise plans when requirements shift, and keep management and partner teams informed and aligned. Build data pipelines and products. Plan and carry out batch and streaming ingestion, transformation, reconciliation, and serving processes for fleet, capacity, utilization, cost, scheduling, and operational telemetry. Establish data models and agreements that remain stable as sources, consumers, and scale progress. Develop shared platform capabilities. Direct the creation and adoption of libraries, workflow and DAG or comparable experience abstractions, deployment tools, and standard implementation approaches. Partner with related teams to solve shared challenges and evaluate progress in onboarding time, engineering effort, reliability, and cost. Lead complex production investigations. Serve as the technical point of accountability for issues spanning pipelines, applications, SQL engines, Spark, storage, networks, and cloud services. Coordinate investigations across owners, drive resolution of release blockers and critical issues from partners, and implement preventive measures. Define quality, security, and operational expectations. Establish and implement testing, data-quality, reconciliation, lineage, SLO, and release-readiness standards for your platform area. Partner with security and infrastructure teams on trust boundaries, service identities, least privilege, secrets, environment isolation, and auditability, and drive adoption across contributing teams. Make trusted data usable. Deliver well-modeled tables, APIs, automation, dashboards, and focused internal applications. Align with consumers on semantics, access patterns, freshness, compatibility, and ownership so that shared capabilities support dependable operational decisions. Provide technical leadership through others. Guide design reviews, mentor engineers taking on larger ownership, and resolve technical disagreements using evidence and clear tradeoffs. Partner with leadership on priorities and explain how technical investments support DGXC objectives. What we need to see: BS or MS in Computer Science, Engineering, or a related field (or equivalent experience), and at least 12+ years of equivalent experience A sustained record of building and operating production software, data platforms, databases, or distributed systems. This includes owning a major component or complex project from requirements and architecture through release and ongoing operation. Proven ability to outline a component’s technical plan, establish objectives for engineers, assign design and implementation tasks, and guide delivery within your team and nearby teams with little supervision. Extensive practical experience in one or more of these areas: distributed processing using Spark or a similar system; relational, distributed, or analytical databases; production ETL, change-data capture, streaming, or event handling; or backend and cloud platforms managing large data volumes. You must grasp the interfaces and failure modes of nearby layers thoroughly to inform solid architectural choices. Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language, with the ability and willingness to work primarily in Python and SQL. Experience designing reusable abstractions, reviewing substantial changes, and personally implementing and debugging critical code paths. Strong SQL and data-modeling skills, with practical depth in query execution, incremental processing, schema evolution, consistency, and analytical consumption. Ability to reason about idempotency, replay, late-arriving data, partial failure, and correctness across system boundaries. Experience leading complex investigations involving multiple components and teams. Ability to use logs, metrics, traces, query plans, profiles, and controlled experiments to establish root cause, coordinate resolution, and prevent recurrence. Demonstrated architectural judgment: evaluating alternatives, anticipating future requirements, and balancing reliability, performance, cost, security, compatibility, and maintainability. Experience leading significant migrations or architectural changes while preserving production service. Experience establishing production quality and operational practices that other engineers adopt, including testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment. Proven success in influencing technical decisions without official authority, advising engineers outside your immediate project, and advancing workflow improvements across closely related teams. Ability to simplify complex issues, offer a course of action, and communicate decisions and delivery risks clearly. Ways to stand out from the crowd: Proven expertise in building, refining, and running Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, or Unity Catalog workloads along with shared platform features. Experience designing and operating Kafka or comparable streaming systems, including partitioning, consumer behavior, offset management, backpressure, replay, and schema compatibility. Experience scaling, migrating, or tuning relational, distributed, time-series, object-storage, or information retrieval systems, including Elasticsearch or OpenSearch. Background operating compute or GPU clusters, or working with Kubernetes, Slurm, cloud infrastructure, and fleet telemetry across AWS, Azure, GCP, or other providers. Experience building production agentic systems or agent harnesses, including tool integration, context management, evaluation, permissions, observability, and failure recovery. Evidence of measurable improvements in engineering productivity or operational outcomes. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 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.

NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. You will be responsible for the architecture, technical plan, and production results of a major platform area like ingestion and orchestration, data quality and reconciliation, or data serving and consumption. You will clarify requirements with customers, define technical objectives, guide design and development among engineers and partner teams, and stay actively engaged in coding, debugging, and production tasks. Successful candidates have already led complex technical work across team boundaries and delivered improvements that other groups adopted. Our primary implementation environment is Python, SQL, Databricks, and Spark. What you’ll be doing: You will own a major platform component and its roadmap. For example, define its architecture, interfaces, technical goals, and evolution. Anticipate capacity, compatibility, and operational needs over a multi-year horizon, and translate them into achievable breakthroughs that balance immediate delivery with long-term maintainability. Lead technical delivery across teams. Work with customers and interested parties to clarify vague requirements. Break down design and implementation work for contributing engineers. Establish release turning points and manage dependencies and delivery risks. Guide the work process, revise plans when requirements shift, and keep management and partner teams informed and aligned. Build data pipelines and products. Plan and carry out batch and streaming ingestion, transformation, reconciliation, and serving processes for fleet, capacity, utilization, cost, scheduling, and operational telemetry. Establish data models and agreements that remain stable as sources, consumers, and scale progress. Develop shared platform capabilities. Direct the creation and adoption of libraries, workflow and DAG or comparable experience abstractions, deployment tools, and standard implementation approaches. Partner with related teams to solve shared challenges and evaluate progress in onboarding time, engineering effort, reliability, and cost. Lead complex production investigations. Serve as the technical point of accountability for issues spanning pipelines, applications, SQL engines, Spark, storage, networks, and cloud services. Coordinate investigations across owners, drive resolution of release blockers and critical issues from partners, and implement preventive measures. Define quality, security, and operational expectations. Establish and implement testing, data-quality, reconciliation, lineage, SLO, and release-readiness standards for your platform area. Partner with security and infrastructure teams on trust boundaries, service identities, least privilege, secrets, environment isolation, and auditability, and drive adoption across contributing teams. Make trusted data usable. Deliver well-modeled tables, APIs, automation, dashboards, and focused internal applications. Align with consumers on semantics, access patterns, freshness, compatibility, and ownership so that shared capabilities support dependable operational decisions. Provide technical leadership through others. Guide design reviews, mentor engineers taking on larger ownership, and resolve technical disagreements using evidence and clear tradeoffs. Partner with leadership on priorities and explain how technical investments support DGXC objectives. What we need to see: BS or MS in Computer Science, Engineering, or a related field (or equivalent experience), and at least 12+ years of equivalent experience A sustained record of building and operating production software, data platforms, databases, or distributed systems. This includes owning a major component or complex project from requirements and architecture through release and ongoing operation. Proven ability to outline a component’s technical plan, establish objectives for engineers, assign design and implementation tasks, and guide delivery within your team and nearby teams with little supervision. Extensive practical experience in one or more of these areas: distributed processing using Spark or a similar system; relational, distributed, or analytical databases; production ETL, change-data capture, streaming, or event handling; or backend and cloud platforms managing large data volumes. You must grasp the interfaces and failure modes of nearby layers thoroughly to inform solid architectural choices. Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language, with the ability and willingness to work primarily in Python and SQL. Experience designing reusable abstractions, reviewing substantial changes, and personally implementing and debugging critical code paths. Strong SQL and data-modeling skills, with practical depth in query execution, incremental processing, schema evolution, consistency, and analytical consumption. Ability to reason about idempotency, replay, late-arriving data, partial failure, and correctness across system boundaries. Experience leading complex investigations involving multiple components and teams. Ability to use logs, metrics, traces, query plans, profiles, and controlled experiments to establish root cause, coordinate resolution, and prevent recurrence. Demonstrated architectural judgment: evaluating alternatives, anticipating future requirements, and balancing reliability, performance, cost, security, compatibility, and maintainability. Experience leading significant migrations or architectural changes while preserving production service. Experience establishing production quality and operational practices that other engineers adopt, including testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment. Proven success in influencing technical decisions without official authority, advising engineers outside your immediate project, and advancing workflow improvements across closely related teams. Ability to simplify complex issues, offer a course of action, and communicate decisions and delivery risks clearly. Ways to stand out from the crowd: Proven expertise in building, refining, and running Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, or Unity Catalog workloads along with shared platform features. Experience designing and operating Kafka or comparable streaming systems, including partitioning, consumer behavior, offset management, backpressure, replay, and schema compatibility. Experience scaling, migrating, or tuning relational, distributed, time-series, object-storage, or information retrieval systems, including Elasticsearch or OpenSearch. Background operating compute or GPU clusters, or working with Kubernetes, Slurm, cloud infrastructure, and fleet telemetry across AWS, Azure, GCP, or other providers. Experience building production agentic systems or agent harnesses, including tool integration, context management, evaluation, permissions, observability, and failure recovery. Evidence of measurable improvements in engineering productivity or operational outcomes. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 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.

NVIDIA is redefining accelerated computing and powering the next era of artificial intelligence. Our data-center platforms bring together GPUs, CPUs, networking, systems, and software to solve some of the world’s most exciting computing problems. We are looking for a System Software Engineer to join NVIDIA’s GPU Performance and Power Management Software team. You will help design, develop, and debug production software for performance states (P-states) and Power Management Controllers. Your work will also support dynamic voltage and frequency scaling (DVFS) and power-management technologies for next-generation data-center GPUs. You will work at the intersection of hardware architecture, embedded firmware, device drivers, operating systems, and AI workloads. In this role, you will contribute across the product lifecycle, including design, pre-silicon development, validation, silicon bring-up, and production support. This is a great opportunity to build expertise in GPU power and performance software while contributing to products that deliver leading performance, energy efficiency, and reliability. What You’ll Be Doing: Design, build, implement, and debug GPU power- and performance-management software, with emphasis on P-state management and DVFS. Develop control policies and software mechanisms that optimize GPU performance, power, thermals, and energy efficiency under demanding data-center workloads. Support features through full product lifecycle: requirements, architecture, implementation, pre-silicon validation, silicon bring-up, productization, and production support. Collaborate with GPU architects and hardware designers to define and implement hardware-software interfaces for next-generation processors. Analyze interactions among workloads, clocks, voltages, power limits, thermals, telemetry, and system-level policies. Investigate, triage, and resolve power, performance, stability, and reliability issues spanning firmware, drivers, hardware, and platform software. Help execute validation strategies and automation for functional correctness, transition latency, performance-per-watt, and robustness across operating conditions. Write clear technical documentation, interface definitions, for features. Partner with distributed teams across architecture, ASIC, firmware, driver, validation, platform, and data-center systems. What We Need to See: BS or MS degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience. 2+ years of relevant industry experience, or strong coursework, internship, co-op, or project experience in system software. Strong programming skills in C, with the ability to develop, debug, and maintain low-level kernel software. Good understanding of operating-system fundamentals, computer architecture, device-driver architecture, embedded or real-time software, concurrency, interrupt handling, and hardware programming Ability to independently debug and analyze across multiple layers of software and hardware. Ability to read and understand hardware specifications and software interface definitions. Strong problem-solving skills and willingness to learn from and work effectively with cross-functional teams. Excellent written and verbal communication skills. Ways to Stand Out From the Crowd: Hands-on, Internship or project experience with GPU, CPU, accelerator, or SoC power and performance management. Coursework or project work in computer architecture, operating systems, control systems, or power/performance optimization. Exposure to P-states, DVFS, clock control, voltage control, thermal management, or workload-aware system behavior. Familiarity with validation, scripting or automation, and telemetry analysis for low-level software features. Strong understanding of hardware-software interactions. Experience with AI tools leverage for SW engineering work - coding, validation, automation workflows 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 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 October 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.

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. The Tegra Team searching for a creative and highly motivated engineer with expertise in system software to join the Tegra system-on-chip (SOC) Software organization. You will design key aspects of our Tegra SoC kernel drivers and embedded Software. This role will be dedicated to advancing ARM SoC on pre-silicon and silicon platforms. Join us to build a world class System software team. What you'll be doing: Design, develop and verify features for our next generation SoC architecture, collaborating with hardware engineers and fellow software engineers. Heavily involved with the early modeling simulation required to produce our outstanding products. Working closely with the hardware, silicon, pre-silicon teams to bring-up new platforms, products, and prototype systems. Involved in SoC bringup with a focus on enabling the core OS software on new platforms. Get to craft, develop, unit test, document and maintain features for Tegra SoCs. You will influence hardware architecture and system software by creating architecture and design specification. What we need to see: BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience 5+ years of relevant software development experience Proven leadership skills and strong ownership on past projects Hands on technical experience and demonstrated excellence in an environment with complex software and hardware designs Outstanding C programming and low-level driver experience; background and strength with complex system-level debugging Experienced with ARM based processor architecture Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.) Ways to stand out from the crowd: Background with Chip or Board bring-up Experience developing high quality embedded code Experience with JTAG and other debugging 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 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 October 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.

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. The Tegra Team searching for a creative and highly motivated engineer with expertise in system software to join the Tegra system-on-chip (SOC) Software organization. You will design key aspects of our Tegra SoC kernel drivers and embedded Software. This role will be dedicated to advancing ARM SoC on pre-silicon and silicon platforms. Join us to build a world class System software team. What you'll be doing: Design, develop and verify features for our next generation SoC architecture, collaborating with hardware engineers and fellow software engineers. Heavily involved with the early modeling simulation required to produce our outstanding products. Working closely with the hardware, silicon, pre-silicon teams to bring-up new platforms, products, and prototype systems. Involved in SoC bringup with a focus on enabling the core OS software on new platforms. Get to craft, develop, unit test, document and maintain features for Tegra SoCs. You will influence hardware architecture and system software by creating architecture and design specification. What we need to see: BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience 5+ years of relevant software development experience Proven leadership skills and strong ownership on past projects Hands on technical experience and demonstrated excellence in an environment with complex software and hardware designs Outstanding C programming and low-level driver experience; background and strength with complex system-level debugging Experienced with ARM based processor architecture Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.) Ways to stand out from the crowd: Background with Chip or Board bring-up Experience developing high quality embedded code Experience with JTAG and other debugging 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 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 October 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.

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. The Tegra Team searching for a creative and highly motivated engineer with expertise in system software to join the Tegra system-on-chip (SOC) Software organization. You will design key aspects of our Tegra SoC kernel drivers and embedded Software. This role will be dedicated to advancing ARM SoC on pre-silicon and silicon platforms. Join us to build a world class System software team. What you'll be doing: Design, develop and verify features for our next generation SoC architecture, collaborating with hardware engineers and fellow software engineers. Heavily involved with the early modeling simulation required to produce our outstanding products. Working closely with the hardware, silicon, pre-silicon teams to bring-up new platforms, products, and prototype systems. Involved in SoC bringup with a focus on enabling the core OS software on new platforms. Get to craft, develop, unit test, document and maintain features for Tegra SoCs. You will influence hardware architecture and system software by creating architecture and design specification. What we need to see: BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience 5+ years of relevant software development experience Proven leadership skills and strong ownership on past projects Hands on technical experience and demonstrated excellence in an environment with complex software and hardware designs Outstanding C programming and low-level driver experience; background and strength with complex system-level debugging Experienced with ARM based processor architecture Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.) Ways to stand out from the crowd: Background with Chip or Board bring-up Experience developing high quality embedded code Experience with JTAG and other debugging 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 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 October 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.

NVIDIA is at the forefront of the generative AI revolution, building the software and systems that power the world’s most advanced large language model workloads. We are looking for a Software Engineer focused on bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales we run. In this role you will help bring up, benchmark, and debug distributed LLM workloads on multi-GPU and multi-node deployments, and own the design and implementation of the benchmarking tooling, automation, and debugging workflows that support them. This is a hands-on role for an engineer who enjoys deep technical problems across deep learning systems, GPU performance, distributed computing, and large-scale operations. What you’ll be doing: Bring up, validate, and debug large-scale AI clusters, infrastructure, and end-to-end workloads. Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks. Perform root-cause analysis of failures in large distributed environments Contribute to the resilience and failure-attribution tooling that detects, triages, and attributes node, fabric, and workload failures across the cluster. Build and maintain repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms. Tune runtime settings, communication parameters, and deployment configurations in close partnership with framework, systems, and platform teams. Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization. What we need to see: Bachelor’s or Master’s in Computer Science or a related technical field (or equivalent experience). Experience developing software for AI, HPC, or systems-level applications. Hands-on experience with multi-GPU or multi-node workloads and CUDA-aware distributed execution. Background with debugging and scaling distributed systems. Experience debugging and triaging AI applications across the full stack, from the application level toward the hardware. Experience operating workloads in scheduled, containerized cluster environments. Excellent analytical, debugging, and communication skills, and a collaborative approach across teams. Strong Python and C/C++ programming skills. Ways to stand out from the crowd: Hands-on experience with NCCL and CUDA-aware distributed execution. Deep familiarity with the RDMA software stack (NCCL, IB verbs, UCX, libfabric) and with InfiniBand / RoCE congestion debugging. Experience building acceptance tests, benchmark harnesses, regression gates, or cluster qualification tooling for AI platforms, including MLPerf. Experience diagnosing performance jitter Experience building resilience, fault-detection, or failure-attribution systems for datacenter-scale 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 love a challenge, 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 108,000 USD - 178,250 USD for Level 1, and 124,000 USD - 195,500 USD for Level 2. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 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.