AI-ML Principal Software Engineer

Based within the R&D department in Saint-Étienne (60 people) and reporting to the System Group Manager, you are experienced, passionate, and a results-oriented Artificial Intelligence and Machine Learning (AI/ML) Engineer ready to drive innovation in the critical field of Fiber Test and Measurement., In this role, you will transform complex network testing challenges into innovative AI-driven solutions across the entire AI/ML lifecycle.

You will:

• Generate and rigorously assess new AI/ML concepts for fiber test and measurement applications.
• Design, build, and rigorously validate AI/ML models for fiber test and measurement applications, writing the code yourself.
• Apply signal processing and statistical analysis techniques (e.g., filtering, spectral analysis, noise characterization) directly to fiber network test data to extract features and inform model design.
• Own the AI/ML and signal processing pipeline end-to-end, from data collection and pre-processing through model development, proofs-of-concept (PoCs) and Minimum Viable Products (MVPs) validation, and integration into production fiber testing and analytics platforms.
• Collaborate with cross-functional, international teams to shape the future of optical network intelligence., Software Skills: Strong programming foundation across data science and production software development, with comfort using AI tools to accelerate workflows.
• Python (Pandas, NumPy, scikit-learn).
• Java (fiber monitoring product software).
• C++ (embedded product software).
• AI agent tools (e.g., Claude Code) for development, testing, documentation.
• Signal Processing: Practical experience applying signal processing and statistical techniques to test and measurement data.
• Filtering, spectral analysis, noise characterization.
• Time series analysis.
• Statistical modeling.
• Optimization.
• AI/ML Pipeline: End-to-end experience across the ML lifecycle, from data handling through model development, deployment, and communication of results.
• Data handling: SQL, structured/unstructured data sources.
• ML frameworks: TensorFlow, PyTorch, Keras.
• Core algorithms: strong understanding of modern convolutional neural networks and transformer architectures (ConvNext, ResNet, U-Net, DETR), supervised learning (regression, classification), unsupervised learning (contrastive learning, clustering, dimensionality reduction).
• Optimization & hyperparameter tuning (e.g., Optuna, Ray Tune, grid/random search).
• MLOps: versioning, testing, CI/CD, model lifecycle management (MLflow, Kubeflow, ONNX).
• Deployment: cloud environments, edge devices for real-time applications (Sagemaker, TensorRT).
• Data visualization for communicating model performance and results to both technical and non-technical audiences (MLFlow, TensorBoard).

• Master’s engineering degree in computer science, Electrical Engineering, Data Science, Artificial Intelligence, or a closely related technical field.
• At least 5 years of AI/ML experience in an industrial R&D environment.
• Collaborative Team Player: Exceptional ability to work effectively and collaboratively within diverse, cross-functional teams with international stakeholders in English and French.
• Communication & Presentation: Excellent written and verbal English & French communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders and prepare clear, concise documentation.
• Problem-Solving & Critical Thinking: Demonstrated strong analytical and problem-solving skills, with a proactive approach to identifying and resolving technical challenges.