Senior Solutions Architect, Autonomous Vehicles - Data Center

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Senior Solutions Architect for Autonomous Vehicles and Robotics to help customers accelerate Physical AI workloads using NVIDIA's full-stack technologies. The role involves engaging with customers to optimize training, simulations, and synthetic data generation for AV perception and planning models, providing technical expertise, and driving full-stack adoption. The candidate will analyze and optimize AI models for GPU performance, build collateral for various AI workflows, and provide technical leadership. Requires 8+ years of ML/DL Infra experience in AVs, proficiency in Python, CUDA/C++, Linux, DevOps tools, and a strong understanding of AV models and simulations. Experience with model deployment at scale and robotics model development is a plus. The role focuses on the data and infrastructure aspects of AI model development and deployment in the AV domain.

What you'd actually do

  1. 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.
  2. 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.
  3. Develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies to customers.
  4. 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.
  5. 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.

Skills

Required

  • 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.

Nice to have

  • 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.

What the JD emphasized

  • 8+ years of hands-on validated ML/DL Infra experience in Autonomous Vehicles with focus on improving compute efficiency of training and inferencing workloads.

Other signals

  • customer-facing technical expertise
  • accelerating AI workloads
  • full-stack technologies
  • autonomous vehicles
  • robotics
  • ML/DL Infra
  • training and inferencing workloads
  • GPU architectures
  • model training and validations
  • LLM, VLA, VLM, World Models