Position Overview At Munich Re, you will help shape and industrialize AI and Generative AI (GenAI) capabilities that support critical decision making across insurance, risk, and reinsurance domains. As a Senior Machine Learning Engineer, you will play a key role in designing, building, and operationalizing ML solutions—working closely with data scientists, engineers, and business stakeholders to turn advanced analytics into measurable business value. You will contribute across the end‑to‑end ML lifecycle: from data ingestion and feature engineering, to model development, deployment, monitoring, and continuous improvement. Your work will span a broad range of enterprise use cases, leveraging large‑scale, heterogeneous data and modern ML engineering practices to deliver reliable, secure, and scalable AI solutions. As a trusted technical expert, you will help set engineering standards, guide architectural decisions, and apply industry best practices to ensure robustness, performance, and regulatory alignment. You will also stay close to emerging trends in AI and GenAI, helping Munich Re responsibly adopt new technologies in a highly regulated, impact‑driven environment. Your Role Implement end‑to‑end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment, and monitoring. Design and implement machine learning pipelines that support high performance, reliable, scalable, and secure ML workloads. Design scalable ML solutions and MLOps architectures using AWS and/or Azure services, and leverage GenAI solutions where applicable. Collaborate with cross‑functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Application Teams) to prepare, analyze, and operationalize data and AI/ML models. Serve as a trusted advisor to internal stakeholders and business partners on AI/ML, GenAI solutions, and cloud architectures. Share knowledge and best practices through mentoring, training, publications, and the creation of reusable artifacts. Ensure solutions meet industry standards and support the advancement of enterprise AI/ML, GenAI, and cloud adoption strategies. Internal job title: Senior Application Developer. Your Profile Bachelor’s, Master’s, or PhD in Computer Engineering, Information Technology, or a related field. 6+ years of experience in cloud architecture and implementation and/or applied research. 7+ years of experience in data, software, or machine learning engineering, with a strong understanding of distributed computing (e.g., data pipelines, distributed training and inference, ML infrastructure design). 3+ years of experience developing platforms for predictive modeling, NLP, and deep learning, with a proven track record of building, hosting, and deploying ML models on cloud platforms (e.g., Azure ML, Amazon SageMaker, or similar services). 3+ years of experience with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficiency with industry‑leading ML frameworks such as TensorFlow and PyTorch. Strong communication and collaboration skills, with the ability to work effectively with senior leaders and stakeholders. Ability to build strong business relationships, negotiate effectively, and confidently articulate technical viewpoints. Hands‑on experience with AWS and/or Azure, including a broad range of AI capabilities (e.g., NLP, IDP, RAG, MLOps). Professional‑level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional). Experience with automation and scripting (e.g., Terraform, Python). Knowledge of security and compliance standards (e.g., HIPAA, GDPR). Experience with modeling and analytics tools such as R, scikit‑learn, Spark MLlib, MXNet, TensorFlow, NumPy, SciPy. Strong communication skills with the ability to explain complex technical concepts to both technical and non‑technical audiences. Proven experience building ML pipelines with best‑practice MLOps, including data preprocessing, feature engineering, model hosting, hyperparameter tuning, distributed and GPU training, deployment, monitoring, and retraining. Experience with MLOps platforms (e.g., MLflow, Kubeflow) and orchestration tools (e.g., Azure Data Factory pipelines, Azure Functions, AWS Step Functions). Experience building applications using Generative AI technologies, including LLMs, vector databases, orchestration frameworks (e.g., LangChain), and prompt engineering. Experience developing Infrastructure as Code (e.g., CloudFormation, CDK, Terraform), containerized workloads, and CI/CD pipelines. About Munich Re Munich Re is the world’s leading reinsurance company with more than 40,000 employees in over 50 locations worldwide. We turn uncertainty into manageable risk, enabling fundamental change. We prioritize diversity, inclusion, and belonging, fostering a culture that welcomes different thoughts and opinions. Our data, technology, and teams uniquely position us to drive transformative change in the life insurance industry. We invest strategically in our world‑class talent, offering a work experience that promotes professional development, innovation, and rewards high performance. What Can We Offer You? An engaging and collaborative environment that promotes continuous learning and development. A hybrid work environment that combines weekly in‑office and remote days. A great compensation package including an annual company bonus. Market‑leading company‑paid flexible health and dental benefits, starting on your first day. Flexible dollars provided by the company to put toward Health Spending Account and/or Wellness Spending Account. Immediate participation in a DC Pension Plan with an automatic employer contribution, plus optional company match. Generous time off—including vacation, personal days, unplanned time, statutory holidays and company‑wide early closure half‑days. Learning and development programs and resources, including unlimited access to LinkedIn Learning, an Education Assistance Program and reimbursement for professional fees. Maternity, parental & adoption leave top‑up program. Employee referral program, recognition & rewards platform. Salary and Location Base salary range: $132,000 to $171,000 per year, plus an opportunity for an annual company bonus based on a percentage of eligible pay. Role located in the Toronto office on 390 Bay St , operating in a hybrid work model. Recruiting Process We do not use AI in our recruitment process—applications are reviewed by our team to ensure a fair and personalized experience. Only candidates selected for interview will be contacted directly. Equal Opportunity Statement Munich Re is committed to providing a work environment that is inclusive and free of employment barriers and discrimination. Accommodations will be made for qualified applicants with a disability throughout the recruitment process. If you receive a request for an interview and you have a disability that will require an accommodation to support your participation, please contact as soon as practical. #J-18808-Ljbffr