Your mission 
L‑Acoustics is looking for an AI Computer Vision apprentice to join our Data & AI department. Under the supervision of the Global Data & AI Director and our Senior AI Engineer, your main mission will be to contribute to the development, deployment, and continuous improvement of advanced vision‑based solutions. 

Responsabilities : 

• Participate in the design and development of computer vision solutions focused on anomaly detection for industrial or innovative use cases. 

• Implement and optimize algorithms for image and video analysis, with a particular emphasis on detecting anomalies, defects, or irregularities in visual data. 

• Contribute to the integration of vision models into production pipelines (APIs, microservices, CI/CD). 

• Conduct technology watch on the latest advances in computer vision and anomaly detection (deep learning, recent architectures, open-source frameworks). 

• Collaborate with business teams (industry) to define needs and translate business problems into technical solutions. 

• Participate in the drafting of technical documentation and presentation of results. 

Qualifications: 

• Master’s student (M2) in computer science, applied mathematics, AI, computer vision, or a related field. 

• Previous experience (internship, academic or personal project) in computer vision or deep learning, ideally with exposure to anomaly detection. 

• Comfortable handling structured and unstructured data (images, videos, annotations). 

• Autonomy, curiosity, rigor, and eagerness to learn. 

Skills: 

• Solid understanding of the fundamentals of computer vision and deep learning, with a focus on anomaly detection techniques. 

• Proficiency in Python and main libraries (OpenCV, PyTorch, TensorFlow, scikit-image, etc.). 

• Knowledge of neural network architectures for vision (VLM, CNN, Transformers, GAN, etc.), with practical experience in anomaly detection methods (autoencoders, one-class classifiers, patch-based detection, etc.). 

• Experience with data management tools (annotation, augmentation, preprocessing pipelines). 

• Familiarity with model deployment (Docker, REST API, cloud platforms such as Azure/GCP/AWS). 

• Sensitivity to data quality, model robustness, and AI ethics. 

• Ability to work in a team, communicate, and explain technical concepts to non-experts. 

Must Have 

• Proficiency in Python for developing computer vision algorithms. 

• Knowledge of deep learning frameworks (PyTorch, TensorFlow). 

• Ability to read and understand scientific articles in English. 

Nice to Have 

• Experience with MLOps tools (MLflow, DVC, model versioning). 

• Knowledge of cloud platforms (Azure, GCP, AWS). 

• Participation in challenges (Kaggle, DrivenData, etc.) or open-source projects. 

• Notions of DevOps and CI/CD. 

• Knowledge of C++ 

Certifications (Nice to Have) 

• Microsoft Azure AI Fundamentals (AI-900) or equivalent. 

Soft Skills:  

• Team spirit, sense of sharing and mutual support. 

• Ability to self-train and stay up to date on innovations in the field. 

• Motivation to contribute to high-impact projects.