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Work on groundbreaking GPU and CPU systems. Understand them across a range of disciplines and identify areas for improvement. Study the applications and models running on Nvidia hardware and their architectural implications.
Driving architectural improvements that simplify and modularize the software stack. Designing clean boundaries between NVIDIA core components and OEM-specific implementations. Refactoring ADAS components to support reuse, extensibility, and long-term maintainability.
Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions.
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.
Develop high-quality code for the Linux kernel and open-source environments, contributing to the upstream kernel community. Collaborate and debug with teams across the globe to provide the best networking solutions for our customers.
Serve as a trusted technical advisor to the next generation of AI-native companies building category-defining applications such as developer copilots, AI search engines, agentic platforms, and multimodal creative tools.
Develop validation test methods for new photonic builds from the Mixed-Signal Compose group. Interact with multi-functional groups to support chip development and validation. Characterize fundamental optical, electro-optical, and RF performance of new chip builds.
Design and implement end-to-end integrations of Grove with open-source AI frameworks (e.g., Dynamo, llm-d, Ray, PyTorch, and related ecosystem projects).
Act as the technical point of contact for startups and developers building agentic, multi-modal applications—or adding AI agents to existing platforms.
Launching products: You'll build and manage launch plans for high-visibility NIM releases, coordinating assets, timelines, keynote slides, demos, and press materials while driving cross-functional execution with product management, engineering, technical marketing, and PR or…
Design new hardware features for future graphics and parallel processing architectures. Develop or enhance graphics or parallel processing algorithms and advance the state of parallel computation.
Drive the engineering contribution strategy across the JAX ecosystem stack — including JAX core, XLA, Shardy, MPMD, and application-level codebases like MaxText — prioritizing where NVIDIA's contributions create maximum impact on performance, adoption, and ecosystem influence.
Work with sophisticated technologies and develop behavioral model and verification for custom mixed signal design cells that would be used on all the NVIDIA products.
Improve reliability, performance, observability, release confidence, and end-user experience across desktop, web, and service-based AI products.
Serve as the lead technical advisor for partners delivering reasoning, multimodal, fine-tuning, and model-serving solutions. Guide partners to the right approach for customer workloads across fine-tuning, distillation, quantization, compression, benchmarking, and evaluation.
Primary responsibilities will include deploying, managing, and validating AI Compute/HPC infrastructure in Linux-based environments for new and existing customers. Be the domain expert with partners during planning calls through implementation.
Proactively identify operational and regulatory issues across the state provision and compliance processes, and resolve them before they become compliance or financial risks.
Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms. Understand the big picture of training performance on GPUs, prioritizing and then solving problems across all state-of-the-art neural networks.
You will be working on architecture and design of our state-of-the-art high speed coherent interconnects (NVLINK-C2C) for our mobile SoCs and GPUs.
Conduct Finite Element Analysis (FEA) to assess stress, warpage, and thermo-mechanical behavior throughout advanced semiconductor packaging platforms.
Explore circuit approaches to optimizing processor computation and interconnect performance and power. Design and implement circuit approaches in prototype systems.
Work on workload bring-up and performance analysis/projection, both on silicon and full-system simulator. Study workloads for a wide range of markets, including AI/DL, CSP, HPC, and autonomous vehicles.
Designing and developing groundbreaking techniques to accelerate high-performance workloads at the intersection of AI, math, and financial systems.
Architect and implement sophisticated data processing pipelines that produce premium-quality training data for Generative AI and Physical AI systems. Design and develop cutting-edge physics simulation algorithms that enhance Physical AI training.
US, USA