Senior Computer Vision Engineer (M/F)

The Inria University of Lille centre, created in 2008, employs 360 people including 305 scientists in 15 research teams. Recognised for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria University of Lille centre pursues a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in digital technologies and provides access to the best European and international research for the benefit of innovation and companies, particularly in the region.

For more than 10 years, the Inria University of Lille centre has been located at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on Avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT).

Relevant Literature

• Deep Learning-enabled Detection and Classification of Bacterial Colonies using a Thin Film Transistor (TFT) Image Sensor
• S.L. Jacques: Polarized light imaging of tissues
• Artificial Intelligence in Dermatology: Challenges and Perspectives | Dermatology and Therapy

Responsibilities :

This position focuses on cutting-edge image analysis in the field of microbiology and dermatology. The recruited engineer will be tasked with creating  algorithms to identify microorganisms in microscopic skin images. They will also be responsible for developing and fine-tuning deep learning models capable of real-time analysis. Additionally, the role involves active participation in the company's data pipeline and model deployment processes, ensuring seamless integration of the developed solutions into the existing infrastructure. This position requires a blend of expertise in computer vision, machine learning, and software engineering, with a specific application in biological

Key responsibilities will include:

• Data collection and annotation: Designing and implementing strategies for gathering and labeling high-quality image datasets specific to the SkinBionics needs.
• Developing algorithms for microorganism detection in microscopic skin images.
• Implementing and optimizing deep learning models for real-time analysis: This involves model evaluation and benchmarking (assessing the performance of different computer vision algorithms and architectures)
• Collaborating with our biology team to improve detection accuracy.
• Contributing to our data pipeline and model deployment processes.

Additional activities:

• Prototype development: Creating rapid prototypes and proof-of-concept models to demonstrate the feasibility of computer vision solutions for the startup's products or services.
• Integration with existing systems: Collaborating with other engineering teams to incorporate computer vision capabilities into the SkinBionics's existing software or hardware infrastructure
• Present the works’ progress to investors.

Technical skills and level required :

Languages :

Relational skills :

• Knowledge of microorganism imaging and analysis (preferred).
• Understanding light-tissue interactions like scattering and absorption (preferred).

Other valued appreciated :

We prioritize candidates who can balance technical expertise with strong communication abilities.

• Subsidized meals
• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking  and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Social security coverage

According to the profile