Search the 51 jobs at NVIDIA

The role involves designing and operating a scalable Software Defined Networking (SDN) service for NVIDIA's Cloud infrastructure. Responsibilities include developing network architectures, ensuring performance and security, crafting Infrastructure-as-a-Service for networking, and overseeing operational aspects of the SDN service. The position requires deep expertise in host networking, Kubernetes, Linux networking, and network monitoring systems.

As a Principal Software Engineer at NVIDIA, you will lead the development of visual AI software, invent and prototype tools and services, optimize production code for GPUs, and collaborate with research teams to advance computer vision technologies. Your role involves mentoring, project planning, and driving innovation in AI applications.

As a Consumer Marketing Specialist at NVIDIA, you will develop and implement marketing strategies, collaborate with teams for campaigns, conduct market research, manage social media, and track performance metrics to enhance product visibility and drive customer interest.

As a Principal Software Architect at NVIDIA, you will enhance GPU Networking for AI workloads, lead architectural designs, conduct proof-of-concept developments, and evaluate new technologies for alignment with business goals, with a focus on high-performance computing and data centers.

As a Senior Compiler Engineer at NVIDIA, you will design, develop, and optimize compilers for AI and HPC workloads. You'll work on improving compiler software for NVIDIA Grace CPUs, collaborate with partners, and engage with open source communities to enhance performance-critical software.

As a Senior Software Architect at NVIDIA, you will design and develop solutions for network programmability, collaborate with various teams on accelerating technologies, and engage in proof-of-concept development across multiple fields related to modern data centers.

The ASIC Verification Engineer will be responsible for verification of IP/Cluster/SOC designs for NVIDIA's Graphics Processors and Tegra SOCs. This includes creating regression plans, performing pre-silicon validation, and ensuring functional coverage. Collaboration with hardware architects, software teams, and post-silicon verification is also required.

The Chip Power Optimization Engineer at NVIDIA develops advanced power models for GPUs and SOCs, estimating power consumption based on various use cases. Responsibilities include collaborating with cross-functional teams to optimize power/performance configurations and contributing to improvements in performance and power efficiency.

The role involves performance analysis of high-performance GPUs and SoCs, developing workloads and test suites for various applications, improving turnaround time in product development, and developing infrastructure for performance simulation and analysis. Close collaboration with architecture and design teams is essential.

The ASIC Design Engineer is tasked with developing and enhancing timing analysis/signoff workflows, managing chip level integration, physically partitioning and floor planning, and optimizing designs. This role includes creating custom timing scripts for clock skew analysis and engaging in design optimization tasks to ensure effective design implementation from micro-architecture to tape-out.

Design and implement SoCs, defining micro-architectures and developing RTL while collaborating with verification teams. Responsibilities include owning silicon bring-up, mentoring junior engineers, and ensuring accurate verification and implementation of features.

As an ASIC Engineer at NVIDIA, you will own the micro-architecture and RTL development of PCI Express Controllers, collaborate with design teams, and ensure correct feature implementation through verification and post-silicon debug. You will work closely with multiple teams to meet performance, power, and area requirements.

This role involves system-level performance analysis of complex GPUs and SoCs, development of performance models and test suits, and collaboration with architecture teams to optimize performance, area, and power. You'll also develop infrastructure for early performance analysis and improve methodologies for data representation.

As an AI Developer Technology Engineer, you will develop and analyze deep learning and AI techniques, optimize performance on GPU architectures, and collaborate with various teams to shape next-gen architectures and software platforms while addressing customer needs.

The Senior Systems Engineer will enhance and scale a cloud compute platform for Autonomous Vehicles, design scalable services, support multiple teams, and ensure effective operations and user support, all while leveraging state-of-the-art technologies and collaboration skills.

Profile and analyze AI workloads on large GPUs and CPUs scale clusters for distributed Deep Learning LLM training with a focus on high-performance networking. Develop performance analysis tools and methodologies to understand performance expectations, limitations, and bottlenecks. Collaborate with cross-functional teams to provide performance analysis insights.

As a Senior ASIC Design Engineer, you will implement and deliver high-performance RTL designs, analyze architectural trade-offs, and collaborate with various teams. You will work with a range of IPs and support silicon validation activities, utilizing your expertise in ASIC design and RTL development.

As a GPU/SOC system software engineer at NVIDIA, you will design, implement, and debug changes in the NVIDIA software stack, focusing on kernel-mode software and collaborating with teams globally. Your role involves working with complex system level interactions and ensuring platform performance and robustness.

The Senior Systems Software Engineer will focus on optimizing AI models and data processing for Windows PCs, collaborating with teams across NVIDIA to enhance GPU performance for AI applications and ensuring effective deployment of automated testing.

As an Operations Research Scientist at NVIDIA, you will develop analytics and optimization models for supply chain decision-making. Responsibilities include designing solutions, leading projects, applying statistical techniques, and conducting quantitative analysis to enhance profitability and market share for the business.