Machine Learning Engineer (Mid–Senior) – 12-Month Freelance Contract (Hybrid – Brussels)AI. Real-World Impact. Not a side project.I'm working with a major European insurer who's investing heavily in AI to transform how risk is modeled, fraud is detected, and claims are processed.They've launched a new program to push advanced machine learning into core insurance systems, and they're assembling a team of hands-on ML engineers to make it happen.This isn't academic research, it's applied ML in a highly regulated, data-rich environment. The RoleWe're looking for a Machine Learning Engineer to design, build, and deploy models in areas such as:Fraud detection across high-volume transactional dataRisk modeling with structured + unstructured datasetsPredictive analytics for claims and customer behaviorNLP-driven automation for documents and claims processing12-month freelance contract, strong extension potential.Hybrid in Brussels, on-site 2–3 days/week for collaboration with product + actuarial teams. What We're Looking ForStrong ML engineers who know how to get models into production.You've built and deployed ML in real-world environments, you understand the trade-offs between theory and application, and you can handle end-to-end pipelines.Must-haves:4+ years in ML engineeringStrong with Python, PyTorch/TensorFlow, MLOps toolingExperience with structured/tabular data, time-series, or NLPSolid grasp of optimisation, performanceBackground in CI/CD, Docker/K8s, cloud or hybrid infraAble to work onsite in Brussels (hybrid, 2–3 days/week) Tech EnvironmentLanguages/Frameworks: Python, PyTorch, TensorFlow, Scikit-learnMLOps/Infra: MLflow, Airflow, Kubernetes, Docker, TerraformCloud: AWS / GCP hybrid environmentsData: SQL/NoSQL, insurance domain data (claims, policy, transactional) Why This Project?Insurance is an industry where ML actuallychanges outcomes,catching fraud before it happens, improving fairness in underwriting, and speeding up claims when customers need it most.Applied ML on massive, complex datasetsAutonomy and ownership from day oneCollaborate with actuaries, data scientists, and product leadsBuild models that make real business and customer impact