Machine Learning Engineer

Join RADAR as a Machine Learning Engineer and help build and develop our ML capabilities. You will collaborate with various teams across the company, design and maintain scalable production pipelines, train and deploy high-quality ML models, optimize feature engineering pipelines, implement model monitoring, and champion best practices. The ideal candidate has 5+ years of experience in building production ML systems, proficiency in Python and ML frameworks, and experience with cloud ML platforms.

• Concevoir et maintenir des pipelines de production évolutifs, fiables et efficaces pour l'ingénierie des fonctionnalités, l'entraînement, la prédiction et le déploiement des modèles.
• Former, valider et déployer des modèles d'apprentissage automatique de haute qualité, en appliquant des techniques avancées pour améliorer la précision de nos produits.
• Mettre en œuvre une surveillance complète des modèles, des pipelines d'entraînement automatisés et des solutions d'observabilité pour maintenir la santé et la performance des modèles.
• Production experience with workflow orchestration tools (Airflow, Dagster, Prefect)
• 5+ years building production ML systems at scale, including feature engineering, training, deployment, and monitoring
• Proficiency with version control (Git) and CI/CD practices
• Expertise in big data processing including SQL optimization and distributed computing (Spark/Dask)
• Hands-on experience with cloud ML platforms (AWS SageMaker, Vertex AI, or Azure ML)
• Strong proficiency in Python and ML frameworks (scikit-learn, PyTorch, XGBoost)
• Experience with MLOps tools (MLflow, Weights & Biases, etc.)
• Bachelor's degree in Computer Science, Statistics, or related field
• Experience with real-time streaming data (Kafka, Flink, Pub/Sub.)
• Research has shown that women & underrepresented minorities are more likely to read lists of requirements and consider themselves unqualified if they don't meet every single one. This list represents what we're ideally looking for, but everyone has unique strengths & weaknesses, and we hire for strength & potential, not lack of weakness