Job Title

Company Description: McDonalds is scaling its global data platform to deliver real-time, actionable insights that enhance operations and elevate customer experience. Through Enterprise Data, Analytics, and AI (EDAA), were enabling a smarter, more connected ecosystemdriven by cloud technology, automation, and intelligent data engineering. The Opportunity: We are looking for aMachine Learning Engineer to develop, train, and deploy machine learning models, ensuring they are accurate, scalable, and production-ready. The ideal candidate has strong hands-on experience in ML model development, deployment, and MLOps practices, with familiarity in data exploration and feature engineering. Key Responsibilities: Develop, train, and evaluate machine learning models, including feature engineering, model selection, and hyperparameter tuning. Deploy ML models into production environments, ensuring scalability, reliability, and maintainability. Design, implement, and maintain model deployment pipelines, including CI/CD workflows, automated testing, and model versioning. Develop and maintain monitoring systems to track model performance, data drift, and system health. Build backend services and APIs to integrate ML models with product systems and applications. Apply best practices in MLOps, ensuring reproducibility, reliability, and efficient model operations. Collaborate with engineers and product teams to deliver high-quality ML solutions. Qualifications Required: Masters degree in computer science, Machine Learning, Data Science, or a related field. 5+ years of experience in ML engineering or related roles. Proven experience in training, developing, and deploying ML models. Familiarity with data exploration, preprocessing, and feature engineering. Proficiency in Python and standard ML/data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.). Experience with API development and backend integration (e.g., FastAPI, Flask, Django,). Strong understanding of MLOps tools and practices, such as MLflow, Kubeflow, Airflow, Prefect, Docker, Kubernetes. Experience building data pipelines, processing workflows, and monitoring deployed models. Preferred: Experience with distributed computing frameworks (Spark, Ray). Familiarity with cloud platforms (AWS, GCP) or platform-agnostic orchestration tools. Experience working in fast-paced, experimentation-driven environments. Knowledge of microservices or event-driven architectures. McDonalds Values: Our shared values create the foundation for how we work: Serve: Customers and people come first Inclusion: All are welcome Integrity: We act with honesty Community: We support and uplift each other Family: We learn and grow together Equal Opportunity Statement: McDonalds believes in equal opportunity and a workplace where everyone belongs. We welcome candidates from all backgrounds and are committed to creating a diverse, inclusive environment where everyone can thrive.