Senior AI Architect, Foundation Models and SoC Co-Design

What you'll do

• Research and forecast emerging AI model architectures like VLA and multimodal foundation models for autonomous vehicles.
• Drive hardware-software co-design for next-generation AI workloads across GPUs, CPUs, DLAs, and memory hierarchies.
• Analyze compute, memory, bandwidth, and latency characteristics of transformers, diffusion models, and MoE systems.
• Influence future silicon and IP design decisions through deep workload characterization and performance analysis.
• Prototype and evaluate emerging model paradigms on NVIDIA DRIVE platforms to validate scalability and deployment feasibility.
• Evaluate tradeoffs between latency, throughput, power efficiency, and safety for production autonomous vehicle systems.
• Define benchmarking methodologies and evaluation metrics for next-generation AV AI systems, including robustness and edge-case performance.

What we're looking for

• MS, PhD, or equivalent experience in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a 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, NVIDIA platforms, silicon architecture influence, and multimodal fusion (preferred).