Two Research Engineer (Piemonte)

Two Research Engineer (Piemonte)

25 ott
|
AI4I Opens Two International
|
Piemonte

25 ott

AI4I Opens Two International

Piemonte

Two Research Engineer / Research Fellow Positions in Edge AI and Intelligent Sensing

AI4I — Italian Institute of Artificial Intelligence, Turin, Italy

Scientific Lead

Location

Positions

2

Working language

As soon as possible.

Compensation

Approximately €33,000 gross per year (±15%), depending on experience, qualifications, and performance.

The Edge AI & Intelligent Sensing (EIS) Laboratory at the Italian Institute of Artificial Intelligence (AI4I) is seeking two Research Engineers / Research Fellows to work at the intersection of Edge AI and emerging sensing technologies .

The EIS Lab is scientifically led by Prof. Michele Magno , Professor at ETH Zurich and internationally recognized researcher in Edge AI, intelligent sensing systems, ultra-low-power embedded computing, and autonomous systems.

The laboratory develops intelligent systems that bring AI directly to the edge, where AI meets the physical world, enabling real-time, reliable, and energy-efficient intelligence on resource-constrained devices and in real-world environments .

We are looking for researchers and engineers who are excited about working across the boundaries of machine learning, embedded systems, sensing, and hardware/software co-design , and who want to translate research ideas into working experimental systems. Research spans application domains including robotics and autonomous systems, wearables, automotive, industrial systems, and biosignal sensing and processing , with a strong focus on real-world deployment and technologies with clear industrial relevance .

The role





Research Engineers / Research Fellows will work closely with Prof. Magno and the EIS research team to design, implement, and experimentally validate new approaches for intelligent sensing and Edge AI.

Responsibilities may include:

- Develop and evaluate machine learning and deep learning methods for edge and embedded applications.
- Work with embedded platforms, edge accelerators, MCUs, NPUs, FPGAs, or other specialized computing hardware.
- Integrate AI algorithms with novel intelligent sensing technologies , including event-based cameras, depth cameras, radars , and other emerging sensing modalities.
- Develop and experimentally evaluate prototypes toward high-TRL solutions , with a strong focus on real-world deployment and industrial relevance , across applications such as robotics, wearables, automotive, and industrial systems.
- Contribute to scientific publications , research prototypes , open-source software, and collaborations with academic and industrial partners .

Who we are looking for

We are looking for candidates with a strong technical and experimental profile who are motivated by the challenge of bringing intelligence to real-world sensing and embedded systems.

Required

- MSc degree in Electronic Engineering, or a closely related field.




- Strong programming skills in Python, C/C++ , or similar languages.
- Practical experience with machine learning or deep learning frameworks, particularly PyTorch or equivalent.
- Strong interest in Edge AI, embedded intelligence, intelligent sensing, computer vision, or related areas.
- Hands-on experimental attitude and the ability to build, test, debug, and evaluate real systems.
- Strong written and spoken English.

Candidates may have 1–3 years of relevant research or industrial R&D; experience , or may be excellent recent MSc graduates with a strong experimental profile.

For recent graduates, evidence of research or technical ability may include a high-quality MSc thesis, research or industrial internship, period abroad, publications, open-source contributions, or significant technical projects.

Nice to have

Experience in one or more of the following areas is highly valued:

- Embedded systems and Edge AI deployment , including experience with MCUs, NPUs, GPUs, FPGAs, or other edge AI accelerators
- Model optimization and efficient inference , including techniques such as quantization, pruning, and deployment on resource-constrained platforms.
- Computer vision and intelligent sensing, including multimodal perception, sensor fusion, event-based cameras, depth cameras, radars, or other emerging sensing technologies.
- Electronics prototyping and debugging, including PCB design and familiarity with laboratory instrumentation such as oscilloscopes and logic analyzers.
- Experience wit

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