Senior Solutions Architect, Autonomous Vehicles - Data Center job opportunity at NVIDIA.



DateMore Than 30 Days Ago bot
NVIDIA Senior Solutions Architect, Autonomous Vehicles - Data Center
Experience: 8-years
Pattern: full-time
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Autonomous Vehicles - Data Center

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degreePhD
loacation US, CA, Santa Clara, United States Of America
loacation US, CA, Santa ..........United States Of America

NVIDIA is building the world’s leading AI company, and we are looking for an expert AV and Robotics Solutions Architect who can help customers accelerate Physical AI workloads using NVIDIA's full-stack technologies! As part of the Automotive Solutions Architecture team, we work with some of the most innovative accelerated computing platforms focused on the development and test of Autonomous Vehicles. A Solutions Architect is the first line of technical expertise between NVIDIA and our Auto customers so you will engage directly with developers, researchers, and data scientists with some the most strategic customers as well as work directly with business and engineering teams on product strategy as it pertains to these customers. Join us in this exciting endeavor! What you'll be doing: Engage with customers to help accelerate training AV perception and planning/policy models, simulations, synthetic data generation, software in the loop testing, at large scale using Nvidia profiling tools Nsight System/Compute and employing libraries and frameworks such as cuDNN, NCCL, Transform Engine, PyTorch, etc. Partner with Sales, Engineering, Product and other Solution Architect teams to drive NVIDIA full stack adoption. Develop a deep understanding of customer workflows and requirements, lead proof-of-concepts evaluations and provide internal feedback to drive continuous product improvements. Develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies to customers. Perform in-depth analysis and optimization of state-of-the art AI models to ensure the best performance on current- and next-generation GPU architectures. Build collateral (notebooks, github repos, demos, etc.) applied to workflows such as model training and validations, LLM, VLA, VLM, World Models, video encoding/decoding, etc. Provide technical leadership to other team members. What we need to see: BSc/MSc/PhD or equivalent experience in Computer Science, Electrical Engineering, Physics, Mathematics, or a related technical field. 8+ years of hands-on validated ML/DL Infra experience in Autonomous Vehicles with focus on improving compute efficiency of training and inferencing workloads. Experience with Python, CUDA, or C++ and proficiency with Linux. Hands-on experience with DevOps tools such as GitLab, Docker, and Kubernetes. Strong understanding of AV L3/L4 related models, reconstruction-based or generative world models, and simulations. Effective verbal/written communication, and technical presentation skills. Ability to communicate your ideas/code clearly through blog posts, GitHub, ppt. Ways to stand out from the crowd: Prior technical leadership experience Solid understanding of CUDA, and experience with Nsight System and Nsight Compute Robotics model development experience Skilled in deploying ML/DL models at scale on cloud computing clusters with GPUs. Development experience with NVIDIA software libraries and GPUs, and profiling. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until January 13, 2026. This posting is for an existing vacancy.  NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse 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.

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