Design, train and validate object detection and tracking models (YOLO, R-CNN, etc.)
Work on the scalability and robustness of image processing pipelines
Participate in productionizing models through MLOps workflows
Collaborate with Data Engineering and DevOps teams for industrialization and cloud/edge deployment
Contribute to technology watch on deep learning architectures and vision frameworks
Ensure the quality, reproducibility and documentation of experiments conducted
Requirements
Degree from an engineering school or equivalent (Master’s/PhD) in Computer Science, Applied Mathematics or AI
At least 5 years of experience in applied Computer Vision
Proficient with a Deep Learning framework (PyTorch, TensorFlow, or equivalent)
Strong experience with object detection and tracking models (YOLO, Faster R-CNN, RetinaNet, etc.)
Experience handling or fine-tuning a vision–language model (VLM) such as CLIP, Gemini, GPT-4, Mistral or equivalent, with an understanding of their limitations and use cases
Proficient in Python and development best practices (testing, version control, packaging)
Knowledge of MLOps principles and industrialization of AI models (monitoring, deployment, data pipelines)
Benefits
Hybrid in Paris: 3 days in the office, 2 days remote per week
Cadre employment contract and RTT (between 8 and 12 days off per year depending on public holidays)
A Mac or PC according to your preference
60% contribution to meal vouchers valued at €9 per working day
€50/month training budget contribution
Comprehensive health insurance (Alan)
Offices located in central Paris (3rd arrondissement)
Annual offsite with the whole team and numerous company events
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
object detectiontracking modelsYOLOR-CNNDeep LearningPyTorchTensorFlowPythonMLOpsvision-language model