AI System Architect – Foundation Software

We’re looking for a visionary AI System Architect to join our cutting-edge R&D hub in Pisa, focusing on next-generation AI for automotive intelligence. You’ll lead an international team, driving breakthrough AI foundation technologies and setting new standards for automotive AI computing platforms.

Key Responsibilities

• Lead AI Inference System Strategy: Define the architecture and technology roadmap for edge AI inference systems, guiding the industry’s direction in automotive AI.
• Optimize Large Model Deployment: Solve critical technical challenges for deploying large AI models in resource-constrained automotive environments, enhancing inference efficiency and performance.
• Ensure AI System Reliability: Develop robust automotive-grade AI system reliability and security frameworks, establishing safety standards for critical intelligent driving applications.
• Drive Heterogeneous Computing Optimization: Create AI acceleration architectures for various computing platforms (Ascend, Kunpeng) to overcome performance bottlenecks and gain a competitive edge.
• Shape the AI Foundation Software Ecosystem: Plan technology roadmaps and ecosystem development for AI foundation software, fostering open innovation and long-term competitive advantages.

Essential Qualifications

• Master’s degree or higher in Computer Science, AI, or related fields.
• 5+ years of experience in AI system architecture or optimization.
• Proficiency in C/C++ or Python.
• Experience with AI foundation software development (edge inference engines, model optimization, quantization, compiler optimization).
• Familiarity with mainstream deep learning frameworks (TensorFlow/PyTorch) and edge inference frameworks.
• Practical experience in AI edge inference engine development and optimization.
• Knowledge of heterogeneous computing (CPU/NPU/GPU) for AI acceleration.
• Understanding of automotive electronics architecture and intelligent cockpit/autonomous driving system requirements.
• Fluent in English.

Preferred Qualifications

• PhD in Computer Science, AI, or related fields.
• 10+ years of experience in AI system architecture or optimization.
• Publications in top-tier conferences or technological patents.
• Experience contributing to renowned AI frameworks or inference engines.
• Expertise in AI compiler optimization, neural network acceleration, or model compression.
• In-depth research in AI inference reliability, security, or privacy protection.
• Proven technical leadership skills.
• Experience in multinational companies.