Edge Models Optimization Research Engineer

Huawei Italy Research Centers; Pisa; On-site; EUR 50,000 - 60,000; Full time

Benefits offered by this job

Access to real-world datasets

Large-scale computing resources

International collaboration opportunities

Career development in impactful technologies

Job summary

Huawei Italy Research Centers in Pisa is seeking a highly motivated researcher to join their AI platform team. The successful candidate will contribute to developing next-generation models for intelligent vehicles, focusing on post-training techniques and efficient architectures.

The position offers a gross annual salary between €50,000 and €60,000, determined by experience and competencies, plus a potential discretionary annual bonus. Join a dynamic team to drive innovation in automotive computing technologies.

Qualifications

• Master or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
• Strong understanding of transformer architectures, large language models, and modern deep learning techniques.
• Experience with PyTorch and distributed training frameworks.

Responsibilities

• Investigate post-training approaches for language and multimodal models.
• Develop and evaluate model compression techniques for performance optimization.
• Benchmark open-source models and collaborate with platform teams.

Skills

Understanding of transformer architectures

Experience with PyTorch

Knowledge of model optimization techniques

Familiarity with distributed training frameworks

Publications in top-tier conferences

Education

Master or PhD in Computer Science, AI, or related field

Job description

Position Summary

Huawei’s Pisa Research Institute is a core innovation hub in the field of automotive software and embedded systems. We are looking for a highly motivated researcher to join our AI platform team and contribute to the development of next‑generation models for intelligent vehicles and edge computing systems. The successful candidate will focus on post‑training techniques, efficient Mixture‑of‑Experts (MoE) architectures, and deployment optimization on resource‑constrained platforms. Working closely with system software, compiler, and hardware teams, the candidate will help bridge cutting‑edge AI research and real‑world automotive applications.

Key Responsibilities

• Investigate advanced post‑training approaches for large language models and multimodal foundation models, including supervised fine‑tuning, preference alignment, reinforcement learning‑based optimization, and knowledge distillation.
• Explore efficient MoE architectures and sparse inference mechanisms that enable high‑quality intelligence under strict latency, memory, and power constraints.
• Develop and evaluate model compression techniques such as quantization, pruning, and low‑rank adaptation, while also optimizing inference performance across heterogeneous computing platforms including CPUs, GPUs, NPUs, and automotive SoCs.
• Benchmark state‑of‑the‑art open‑source models, collaborate with software platform teams to improve deployment efficiency, and contribute to research publications, patents, and technical innovation initiatives.

Basic Qualifications

• Candidates should hold a master or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, or a closely related field.
• A strong understanding of transformer architectures, large language models, and modern deep learning techniques is required.
• Experience with PyTorch and distributed training frameworks is expected, while previous research experience in model optimization, efficient AI, edge AI, or foundation models will be highly valued.
• Publications in top‑tier conferences or demonstrated open‑source contributions are considered a strong advantage.

What We Offer

We offer an exciting career opportunity to contribute to shaping the future of automotive computing. You will join a multidisciplinary research team working on some of the most challenging topics in AI, software systems, and intelligent vehicles, driving innovation in next‑generation mobility technologies. The position provides access to real‑world datasets, large‑scale computing resources, international collaboration opportunities, and a clear pathway to transform scientific research into impactful technologies deployed at scale.

We offer a gross annual salary typically ranging from €50,000 to €60,000 determined according to objective criteria such as professional experience, competencies, and seniority. Employees may also be considered for a discretionary annual bonus ranging from 0 to 2 monthly salaries, subject to company evaluation. The applicable collective bargaining agreement is the CCNL Telecommunications, within level 6°.