英伟达Senior Solutions Architect, Spectrum-X Low Level
任职要求
• 8+ years of experience with real time embedded computer software, knowledge of Linux kernel, Ethernet and IP protocols • B.Sc, Masters, or Ph.D. in Computer Science, Electrical Engineering, or related technical field (or equivalent experience) • Extensive knowledge in, and experience with debugging issues • Strong analytical and problem-solving skills, with attention to details • Ability to work collaboratively and be willing to work directly with customers • Proven experience with Firmware level code development for Networking products Ways to stand out from the crowd: • Coding development experience with multiple programming languages (from low-level C programming language to high-level languages such as Perl, python, and shell scripts) • Knowledge in Cloud infrastructure and AI workflows • Linux Environment and Linux Networking • Familiarity with NVIDIA DPUs, RoCE, and RDMA concepts NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. The high-speed networking solutions enable GPUs for large scale deployments. Our work opens new universes to explore, enables outstanding creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous vehicles. NVIDIA is looking for excellent people like you to help us accelerate the next wave of artificial intelligence.
工作职责
NVIDIA networking designs and manufactures high-performance networking equipment that enable the most powerful super computers in the largest data centers in the world. With a distributed collection of NVIDIA GPUs inter-connected by networking solutions such as InfiniBand, Ethernet, or RoCE (RDMA over Converged Ethernet) we make powerful ML/AI platforms possible. We are seeking motivated, personable, and independent individuals to join our team!We seek experienced software embedded engineers to help support our groundbreaking, innovative technologies that make AI workloads in large clusters even more performant. As a networking Sr. Solutions Architect at NVIDIA you will have agency and palpable effects on the business, and work closely with customers and R&D teams. What you’ll be doing: • Support networking technologies such as Spectrum-X and work with customers on their technical challenges and requirements using said technologies during pre-sales activities • Develop proof-of-concept materials for innovative technologies for use by early adopters • Gain customers’ trust and understand their needs to help design and deploy groundbreaking NVIDIA networking platforms to run AI and HPC workloads • Address sophisticated and highly visible customer issues • Work closely with R&D teams to develop new features for customers • Help with product requirements alongside engineering and product marketing
NVIDIA networking is a world-leader fast-growing company which supports the most powerful super computers and the largest data centers in the world. We make outstanding artificial intelligence happen with NVIDIA GPUs that accelerate the computing platform and networking solutions based on InfiniBand, Ethernet, or RoCE (RDMA over Converged Ethernet). We believe in our people and products and seek excellent people to join us!The Networking Solutions Architects team is looking for a hardworking, keen software networking engineer to join the team and support the Spectrum-X networking platform which is a revolutionary solution for building multi-tenant, hyperscale AI clouds with Ethernet. As a Networking Solutions Architect you will have a real impact on the business, while working closely with our customers, marketing and R&D teams. What you’ll be doing: • Work as customer technical specialist to address customer requirements and technical challenges during the pre-sales activities of the Spectrum-X solution. • Run and own proof of concept activities introducing our products and integrating them to new and existing accounts. • Support numerous levels of software running on NVIDIA's Ethernet Switches and BlueField Smart NIC. • Debug networking and performance issues and provide solutions to customers. • Work closely with our R&D teams to solve customer issues • Participate in building SW products roadmap by providing customer product requirements and feedback to engineering and marketing teams.
• Primary responsibilities will include building AI/HPC infrastructure for new and existing customers. • Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting. • Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement. • Maintain services once they are live by measuring and monitoring availability, latency, and overall system health. • Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.
• Design, implement, and optimize scalable ML training pipelines for training multimodal foundation models for robotics. • Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines. • Implement scalable data loaders and preprocessors for multimodal datasets, such as videos, text, and sensor data. • Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets. • Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows on large GPU clusters.
• Develop and maintain simulation environments built on frameworks like MuJoCo, and Isaac Lab to support robotics research. • Implement and test control algorithms and XR teleoperation interfaces for simulated robots. • Build procedural generation pipelines for diverse environments, object layouts, and robot motions. • Optimize GPU-based physics simulator performance for large-scale training workloads. • Import, configure, and validate robot assets in USD format, ensuring successful sim2real transfer. • Implement Sim2Real pipelines and deploy learned models to physical robots.