Machine Learning Engineer Fiche de poste

We are seeking a Machine Learning Engineer to bridge the gap between research and production — building systems that train, deploy, and monitor ML models at scale. You will work alongside data scientists and engineers to bring models from notebooks into reliable, performant production systems that deliver measurable business value.

Responsabilités

• Design and implement ML pipelines covering data ingestion, training, evaluation, and deployment
• Build and maintain MLOps infrastructure for model versioning, monitoring, and retraining
• Collaborate with data scientists to productionize models from experimentation to serving
• Develop and maintain model serving infrastructure optimized for latency and throughput
• Implement model monitoring systems to detect drift, degradation, and anomalies
• Build feature engineering pipelines and feature store integrations
• Evaluate and integrate LLMs, embedding models, and RAG architectures
• Document model cards, system designs, and technical decisions

Exigences

• 3+ years of machine learning engineering or applied ML experience
• Strong Python skills with hands-on experience in PyTorch or TensorFlow
• Experience deploying and serving ML models in production environments
• Familiarity with MLOps platforms (MLflow, Weights & Biases, SageMaker)
• Solid understanding of software engineering principles (testing, CI/CD, code review)
• Experience with cloud platforms and containerization (Docker, Kubernetes)
• Strong grasp of ML fundamentals — model evaluation, regularization, feature engineering

Atouts supplémentaires

• Experience with LLMs, fine-tuning, or RAG pipelines
• Knowledge of distributed training frameworks
• Experience with vector databases (Pinecone, Weaviate, Chroma)
• Background in NLP, computer vision, or recommender systems