Edge AI Optimisation Engineer for Automotive Systems

IC Resources; Pisa; In loco; EUR 65.000 - 100.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive salary

Bonus

Full benefits

Descrizione del lavoro

IC Resources in Pisa is seeking a Software Optimisation Research Engineer - Edge to join its R&D centre. You will develop next generation models for intelligent vehicles and edge AI computing, bridging state-of-the-art research with practical automotive applications.

The ideal candidate holds a PhD in CS/AI/CE and several years in R&D for system software. You will work across CPU/GPU/NPUs, transformers, LLMs, and distributed training, collaborating with software, hardware and compiler teams to

Competenze

• PhD in Computer Science, AI or Computer Engineering required.
• Several years of research and development experience in system software.
• Experience with model optimisation and edge AI.
• Familiarity with LLMs and transformer architectures.
• Exposure to distributed training frameworks and deep learning.

Mansioni

• Develop next generation models for intelligent vehicles and edge AI computing.
• Bridge AI research with real-world automotive applications across teams.
• Collaborate with system software, hardware and compiler teams to optimise performance on edge devices.
• Explore optimisation across CPUs, GPUs, NPUs and automotive SoCs.

Conoscenze

Model optimisation

Edge AI

Edge devices

Efficient AI

Neural networks

Distributed training

LLMs

Transformer architectures

Deep learning

Automotive SoCs

Formazione

PhD in Computer Science, AI or Computer Engineering

Descrizione del lavoro

IC Resources in Pisa is seeking a Software Optimisation Research Engineer - Edge to join its R&D centre. You will develop next generation models for intelligent vehicles and edge AI computing, bridging state-of-the-art research with practical automotive applications.

The ideal candidate holds a PhD in CS/AI/CE and several years in R&D for system software. You will work across CPU/GPU/NPUs, transformers, LLMs, and distributed training, collaborating with software, hardware and compiler teams to