Software Optimisation Research Engineer - Edge Models

IC Resources; Pisa; In loco; EUR 90.000 - 130.000; Tempo pieno

Vantaggi offerti da questo lavoro

Bonus

Full benefits

Descrizione del lavoro

IC Resources is seeking a Software Optimisation Research Engineer - Edge for a leading automotive software innovator, based at their R+D Centre in Pisa, Italy. You will develop next‑gen models for intelligent vehicles and edge AI computing, collaborating with system software, hardware and compiler teams to bridge cutting‑edge AI research with real-world automotive applications.

A PhD in Computer Science, AI or Computer Engineering and several years of R&D experience in system software are

Competenze

• PhD in CS/AI/CE with several years of R&D in system software.
• Experience in model optimisation, edge AI and edge devices.
• Knowledge of LLMs, transformer architectures and modern deep learning.

Mansioni

• Develop next-generation models for intelligent vehicles and edge AI computing.
• Collaborate with system software, hardware and compiler teams to bridge AI research with automotive applications.

Conoscenze

Edge AI

Model optimisation

Neural networks

Distributed training

Transformer models

Deep learning

Formazione

PhD in Computer Science/AI/CE

Descrizione del lavoro

This leading developer of emerging automotive software and systems urgently seek a Software Optimisation Research Engineer - Edge to be based at their R+D Centre in Pisa. The Software Optimisation Research Engineer - Edge will be responsible for developing next generation models for intelligent vehicles and edge AI computing systems. Working closely with system software, hardware and compiler teams the Software Optimisation Research Engineer - Edge will be bridging cutting edge AI research and real-world automotive applications.

You will have successfully completed your PhD in Computer Science, AI or Computer Engineering you will have gained several years of experience in research and development for system software applications. You should have experience of model optimisation, edge AI, edge devices, efficient AI, Neural Networks and some exposure to distributed training frameworks. You should also have knowledge of LLMs, transformer architectures and modern deep learning applications. Any exposure to optimising performance across CPUs, GPUs, NPUs or automotive SoCs would be beneficial

The successful candidate can expect a dynamic, inclusive work environment coupled with the flexibility needed for a full work – life balance. On offer you will find a competitive salary, bonus and full benefits.