Senior AI Architect, Foundation Models and SoC Co-Design – Autonomous Vehicles

NVIDIA is at the forefront of accelerated computing, AI, and autonomous machines. From generative AI to robotics and self-driving vehicles, our technologies are transforming some of the world’s largest industries. NVIDIA DRIVE™ is redefining autonomous mobility through state-of-the-art AI, high-performance compute, and scalable software-defined architectures.

• Research and forecast emerging AI model architectures that are expected to shape the future autonomous vehicle stack, including Vision-Language-Action (VLA) models, Multimodal foundation models and more.
• Drive hardware-software co-design across next-generation AI workloads and NVIDIA embedded SoCs, including GPU, CPU, DLA, memory hierarchy, interconnects, and accelerator subsystems.
• Analyze compute, memory, bandwidth, and latency characteristics of sophisticated AI architectures such as transformers, diffusion models, or MoE systems.
• Develop architectural insights and influence future NVIDIA silicon, IP, and system-level design decisions through deep workload characterization and performance analysis.
• Prototype and evaluate emerging model paradigms on NVIDIA DRIVE and embedded AI platforms to validate scalability, efficiency, and deployment feasibility.
• Partner closely with AI research, autonomous driving software, compiler, runtime, and hardware architecture teams to align long-term roadmap and platform strategy.
• Evaluate tradeoffs across latency, throughput, power efficiency, safety, and real-time constraints in production AV systems.
• Define benchmarking methodologies and evaluation metrics for next-generation AV AI systems, including robustness, safety, calibration, and edge-case performance.

• MS, PhD, or equivalent experience in Computer Science, Electrical Engineering, Machine Learning, Robotics, or related field.
• 12+ years of experience in AI/ML systems, deep learning architecture, or hardware/software co-design.
• Deep expertise in modern AI architectures and large-scale model systems.
• Experience mapping AI workloads onto heterogeneous compute architectures including GPUs, CPUs, NPUs/DLAs, DSPs, and memory subsystems.
• Solid understanding of distributed training systems, scaling laws, and inference optimization techniques.
• Experience with model optimization methods such as quantization, sparsity, pruning, distillation, and memory-efficient inference.
• Understanding of performance profiling, systems bottleneck analysis, and workload characterization.

• Experience with autonomous vehicle or robotics stacks including perception, planning, prediction, or control.
• Deep familiarity with NVIDIA platforms such as DRIVE™, Jetson™, CUDA®, Tensor
  
  RT™, Triton, or Tensor
  
  RT-LLM.
• Experience influencing silicon architecture or collaborating directly with hardware design teams.
• Expertise in sophisticated AI efficiency techniques such as FP8/FP4 inference, Mixture-of-Experts routing, Streaming attention and KV-cache optimization.
• Strong understanding of multimodal fusion across camera, lidar, radar, HD maps, and language inputs.

We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous, and passionate about building the future of AI and autonomous systems, we want to hear from you. Come join our team and help shape the next generation of AI computing platforms powering autonomous machines worldwide.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 327,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 5, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.