successfactors
Machine Learning Engineer
Zurich Insurance Company Ltd.
Toronto, CAN
Mid
Onsite
Discovered 4 days ago
pythonsql
Key Skills for This Role
pythonsql
Full Job Posting
What you will do
- Areas of Specialization Candidates may align with one area; experience across all four is not expected. Machine Learning Engineer - Applied AI Build/productionize predictive ML/AI: classification, regression, forecasting and clustering. Build feature pipelines; establish training, validation/testing and bias/fairness testing. Evaluate models; move experiments to production and optimize inference. Assess approved A/B, shadow or controlled pilots; monitor data quality, performance/drift and troubleshoot production issues. Document assumptions, limitations, versions, training-data references and approvals. Relevant experience: statistical ML; scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM or CatBoost; feature engineering; model evaluation; time-based validation; leakage prevention; imbalanced datasets; calibration; experiment tracking; batch/real-time inference. Machine Learning Engineer - Generative AI Engineer, evaluate and productionize enterprise GenAI using foundation models, retrieval and agentic patterns. Build LLM services and RAG pipelines covering ingestion, parsing, cleaning, chunking, embeddings, indexing/retrieval. Evaluate keyword, semantic-vector/hybrid search, filtering/reranking; design prompts, structured outputs/context management. Improve groundedness through retrieval quality, grounding checks, citations, abstention and human review. Build controlled agentic workflows/tool integrations; evaluate retrieval, answers, safety, agent behaviour/business outcomes. Monitor quality, groundedness, safety, latency, reliability/cost; apply access-aware retrieval, sensitive-data controls and prompt-injection defences. Maintain auditable model, prompt, data, index and evaluation records. Relevant experience: Azure OpenAI or comparable platforms; RAG; embeddings; vector indexes; BM25; semantic/hybrid search; retrieval/LLM evaluation; prompt engineering; FastAPI; LangGraph, LangChain, Semantic Kernel, Langfuse or OpenTelemetry. Machine Learning Engineer - Data & ML Platforms Build/operate enterprise-scale data, feature and engineering foundations for ML/AI. Develop training and batch/real-time inference pipelines, reusable feature frameworks and batch/streaming components. Optimize Spark/distributed processing; build secure data-platform/AI interfaces and reusable libraries/templates. Implement ML dataset quality monitoring; support feature management, lineage/reproducibility. Engineer large-scale structured/unstructured data; deploy, monitor and troubleshoot production ML data pipelines. Relevant experience: Databricks, Spark/PySpark, Delta Lake, Python, SQL, batch/streaming architectures, feature management, data-quality testing, lineage, cloud storage/compute, CI/CD and infrastructure as code. MLOps Engineer Build/operate platforms, automation and controls across the ML/AI lifecycle. Design CI/CD for models/AI applications; establish model registration, versioning, lineage/promotion. Build reproducible training/deployment environments; support staged releases, shadow deployments/rollback. Monitor health, latency, data quality, model performance/drift; develop retraining/redeployment workflows with validation/approvals. Manage ML infrastructure/configuration; implement access controls, audit trails/governance evidence and reusable MLOps standards. Relevant experience: MLflow, Databricks, Azure Machine Learning, Azure DevOps, GitHub Actions, Python, REST APIs, Docker, Kubernetes, Terraform, model registries and production observability. What you bring to the table Across the AI Engineering practice, relevant qualifications include: Python and SQL skills. Software engineering fundamentals including Git, APIs, testing and CI/CD. Understanding of ML concepts and the model-development lifecycle. Experience with data processing and analytical workloads. Experience in cloud-based development environments. Understanding of reliable, maintainable, production-ready solutions. Depending on your specialization, the following are assets: Databricks, MLflow and Apache Spark/PySpark. Microsoft Azure or equivalent AWS/Google Cloud technologies. Azure DevOps or GitHub. Docker and containerized applications. REST APIs. scikit-learn, PyTorch, TensorFlow or comparable ML/deep-learning frameworks. Azure OpenAI or comparable managed AI platforms. RAG, embeddings, retrieval and LLM evaluation. Infrastructure as code, Kubernetes and production observability. Security, privacy, Responsible AI and model governance in a regulated environment.
Experience
- Levels Junior Work on defined ML/AI engineering tasks with guidance. Write reliable Python and SQL. Develop/test components within established architecture and engineering patterns. Understand core ML and software-engineering practices. Participate in code reviews and troubleshooting. Learn Zurich's AI engineering, security and governance standards. Intermediate Independently design/deliver ML/AI components and solutions. Own development through production implementation. Make appropriate engineering and technology choices. Troubleshoot complex data, model and production issues. Contribute to architecture and engineering standards. Mentor junior team members. Work with stakeholders to refine technical requirements. Senior Lead design/engineering of complex enterprise AI/ML solutions. Make architecture and technology decisions. Establish reusable patterns and engineering standards. Lead production-readiness, scalability, reliability and security decisions. Mentor engineers and provide technical leadership. Drive engineering excellence through design/code reviews. Partner with architecture, security, governance and business leadership. Evaluate emerging AI technologies and appropriate enterprise adoption patterns.
About Zurich Insurance Company Ltd.
Apply for this job in 1 click
Skip the repetitive application forms
Install the Base Career Chrome Extension and autofill job applications across major job boards with your profile.
Trusted by over 500,000 job seekers on Base Career
More from this employer
More jobs at Zurich Insurance Company Ltd.
Underwriting Specialist - Construction Property
Chicago, USA
Discovered Today
Claims Advisor
, AUS
Discovered Today
Underwriter Trade Credit Insurance (m/w/d)
, USA
Discovered Today
Duales Studium TH Köln Risk and Insurance (m/w/d)
, USA
Discovered Today
Ausbildung Kaufmann/ Kauffrau für Versicherungen und Finanzanlagen Köln (m/w/d)
, USA
Discovered Today
Health Underwriter - Zurich Asuransi Indonesia
, USA
Discovered Today
Underwriter or Underwriting Specialist - Zurich ES
New York City, USA
Discovered Yesterday
Customer Care Representative
Stevens Point, USA
Discovered Yesterday