Principal AI Architect – Generative & Edge (Automotive)

PER International; San Jose (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Relocation support

Job summary

PER International in San Jose, CA is partnering with a top-five semiconductor firm to hire Principal Engineer / Architect for Generative AI & Edge Systems in Automotive. The role focuses on developing GenAI and edge AI solutions for in-vehicle systems, collaborating across silicon, software, and automotive teams to deploy production-ready AI on constrained edge hardware.

You'll lead end-to-end optimization of LLMs for on-device deployment and drive research-to-production transitions in an agile,

Qualifications

• Master's degree in a related field and 10+ years software engineering experience, including GenAI/LLM systems.
• Hands-on with ML/DL frameworks and edge inference toolchains.
• Experience optimizing models for edge deployment with latency/memory considerations.

Responsibilities

• Research and develop GenAI and deep learning-based edge systems for in-vehicle domains (Infotainment, Speech, UI, multimodal ADAS).
• Lead integration of GenAI frameworks optimized for automotive edge compute and production deployment.
• Collaborate with silicon and software teams to define GenAI/LMM solutions with edge feasibility as a core constraint.
• Own end-to-end LLM optimization for on-device deployment on GPUs/NPUs, including quantization, pruning, and distillation.
• Track advances in edge AI and translate breakthroughs into deployable in-vehicle improvements.

Skills

GenAI/LLM systems

Edge AI optimization

C/C++/Python

Education

Master's degree in CS/EE/Math

Tools

TensorFlow

PyTorch

TensorRT

CUDA

ONNX Runtime

Job description

PER International in San Jose, CA is partnering with a top-five semiconductor firm to hire Principal Engineer / Architect for Generative AI & Edge Systems in Automotive. The role focuses on developing GenAI and edge AI solutions for in-vehicle systems, collaborating across silicon, software, and automotive teams to deploy production-ready AI on constrained edge hardware.

You'll lead end-to-end optimization of LLMs for on-device deployment and drive research-to-production transitions in an agile,