Machine Learning Engineer

Responsibilities

• Design, develop, and deploy machine learning models for real-world business use cases
• Preprocess and analyze large datasets to extract actionable insights
• Collaborate with data scientists, engineers, and stakeholders to define ML project scope and objectives
• Optimize model performance and ensure scalability in production environments
• Maintain clear documentation and communicate findings to both technical and non-technical audiences
• Monitor and troubleshoot model performance post-deployment
• Stay up-to-date with latest ML tools, trends, and best practices

Requirements

• Proven experience as a Machine Learning Engineer or similar role
• Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
• Hands-on experience with data pipelines, model training, evaluation, and deployment
• Solid understanding of statistics, data structures, and algorithms
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)
• Experience with MLOps tools is a plus (e.g., MLflow, DVC, Airflow)
• Ability to work independently and manage time effectively in a hybrid work setting
• Fluent in English; French or Dutch is a plus

Nice to Have

• Experience with NLP, computer vision, or time series forecasting
• Background in data engineering or software development
• Previous work in finance, healthcare, or logistics sectors