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As an engineering-driven organization, you will be at the forefront of the company's key technology development. To make this possible, our deployables need to move from hand-built prototypes to a repeatable, qualified production line.
Hands-on experience with test automation, production testing, and automation frameworks. Solid understanding of Linux, embedded systems, firmware, and hardware/software integration.
Establish yourself as a technical specialist in AI networking products, specifically the BlueField DPU and ConnectX product lines. Architect, design, and develop innovative, scalable, and high-performance hardware-accelerated software solutions.
Translate public-sector mission goals, data constraints and operational requirements into technical architectures for generative and agentic AI solutions. Collaborate with partners to build and demonstrate working prototypes using Python and PyTorch.
This role drives AI solutions from discovery and scoping through post-training, harness optimization, and deployment, working alongside partners and customers.
Define and take responsibility for the complete platform architecture covering NICs and network management for computing clusters and data-centers. Drive the strategic vision for coordinated platform solutions addressing AI training/inference and cloud-native workloads.
Work with Cloud Service Providers to design, build, and demonstrate scalable AI training solutions using NVIDIA hardware and software.
Design, develop, test, debug, and optimize creative solutions for GPU firmware throughout the entire GPU lifecycle. Work closely with hardware, software, infrastructure, and business teams to transform new firmware features from idea to reality.
Researching and designing multimodal search and curation systems optimized for Physical AI data — video, lidar, radar, text, and more.
Develop and maintain extensive technical knowledge in Retail & CPG intelligent stores and Physical AI.
You can expect be heavily involved through all aspects of development of our world-class products, ranging up front from design feedback, early modeling, simulation of hardware in pre-silicon environments, all the way through to early silicon bringup and final feature…
As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best compute platform in the world.
We are looking for an Applied Research Scientist to join our computational engineering applied research team!
Integrate learned driving models with vehicle interfaces, sensor inputs, localization, mapping, safety systems, and other autonomous driving components. Establish clear model input, output, timing, state-management, and runtime interface contracts.
Partner directly with leading research labs, researchers, and university faculty as a trusted technical advisor: develop a keen understanding of their scientific goals and drive joint research projects at supercomputing scale.
Drive timing analysis and closure for DFT logic on all Nvidia chips (GPUs/CPUs/DPUs/LPUs/SoCs) at all hierarchical levels (block/cluster/full-chip).
Safety Benchmarking: Design and maintain safety benchmarks for large language and multimodal models, translating risk scenarios into test cases, datasets, and scoring rubrics.
Guide the creation of RTOS firmware operating on embedded microcontrollers within NVIDIA SoCs and GPUs.
Build and support Transformer Engine, the open-source library for accelerating the training of Large Language Models. Collaborate on systems research that improves Deep Learning model performance, such as training using extremely low precision, parallelism methods, etc.
As a member of our team, you will apply your design, coding expertise , and creativity, and to collaborate with peers across NVIDIA to deliver upon the best compute platform in the world.
Define and drive SoC-level RAS hardware architecture across CPUs, interconnects, memory systems, IOs, safety islands, firmware interfaces, and platform-level components.
In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications.
In this role, you will be a leader in a cross-functional team working to implement quantum computers using neutral-atom-based quantum processors. You will be involved in all stages of the electronics product lifecycle for these systems.
Lead, coach and develop a team of Enterprise Account Executives to achieve revenue goals, and hire to build out the team as we grow. Partner with the Director of Sales and other Enterprise Sales Managers to iterate, innovate, and carry out our strategic sales plan.
New York City, USA
France
Germany, Germany