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

Job Summary

NVIDIA is seeking a Senior AI Architect to lead the development of AI model paradigms for autonomous vehicles. This role requires expertise in AI/ML systems, deep learning architecture, and hardware/software co-design.

About the Role

This is a strategic position focusing on AI research, hardware-software co-design, and the integration of AI workloads with NVIDIA's future embedded SoC architectures.

Responsibilities

• Research and forecast emerging AI model architectures for autonomous vehicles, including Vision-Language-Action (VLA) models, Multimodal foundation models, and others.
• 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 like transformers, diffusion models, or MoE systems.
• 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.

Requirements

• 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.

Qualifications

• Experience with autonomous vehicle or robotics stacks including perception, planning, prediction, or control.
• Deep familiarity with NVIDIA platforms such as DRIVE™, Jetson™, CUDA®, TensorRT™, Triton, or TensorRT-LLM.
• Experience influencing silicon architecture or collaborating directly with hardware design teams.
• Expertise in sophisticated AI efficiency techniques (e.g. 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.

Benefits

Base salary range: $208,000 - $327,750 USD. Eligible for equity and benefits.

Pay

Base salary will be determined based on location, experience, and the pay of employees in similar positions.

Schedule

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

Company Information

NVIDIA is committed to fostering an inclusive work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees.