Hiring: Machine Learning Engineer Company: Manulife Location: Toronto, Ontario, Canada Job Posted Time: 2026-09-16 09:39:02 Target Skills & Keywords : Azure, Azure DevOps, CI/CD, Data Pipeline, Databricks, Docker, ETL, Fine-tuning, GitHub Actions, HTML, Infrastructure as Code, Java, Jenkins, Kubernetes, LLM, LangChain, MLOps, MLflow, Machine Learning, OpenAPI, PaaS, Python, RAG, Scala, Segment, Spark, Terraform, TestNG, Vault About the job Experience: •4 years of experience in machine learning engineering, with a proven track record of building and deploying ML models and systems in production. •At least 4 years of experience in machine learning engineering, with a proven track record of building and deploying ML models and systems in production. Required Skills: •Reusable Patterns and Accelerators: Build reusable patterns for data, ML, and GenAI workloads, following MLOps, LLMOps, and AIOps best practices, and partner with delivery teams on implementation. •CI/CD: Own the engineering backbone for ML delivery, including source control workflows, build and deployment pipelines, automated testing, spec-driven development, and release management. •Infrastructure as Code: Provision and manage PaaS infrastructure using Terraform, with repeatable, version-controlled environments across development, staging, and production. •Credential and Secrets Management: Implement secure credential handling using Azure Key Vault and managed identities, scoping access narrowly across services and pipelines. •Scalable Infrastructure: Develop and maintain scalable ML platforms and serving infrastructure that support training, inference, monitoring, and lifecycle management of models in production. •Data Pipeline Optimization: Partner with data engineers to build high-quality, well-tested feature and training pipelines that ensure efficient, reliable data processing for ML applications. •Model Development and Deployment: Design, train, evaluate, and deploy machine learning models, and integrate large language models where they are the right tool, to solve complex business problems and improve operational efficiency. •Model Performance and Reliability: Continuously monitor and improve models and systems for accuracy, latency, cost, drift, and reliability, with clear observability and alerting. Qualifications: •Professional Experience: At least 4 years of experience in machine learning engineering, with a proven track record of building and deploying ML models and systems in production. •Technical Proficiency: Strong programming skills in Python with hands-on experience in ML frameworks and libraries. Experience with Java or Scala for model serving and JVM-based pipelines is an asset, as is familiarity with GenAI tooling such as LangChain, LangGraph, or the OpenAI SDK. •MLOps and CI/CD: Practical experience with model lifecycle tooling (for example MLflow, Azure Machine Learning, or Databricks) and with CI/CD pipelines using tools such as Jenkins, GitHub Actions, or Azure DevOps. •Cloud and Infrastructure: Working knowledge of cloud platforms, containerization (Docker, Kubernetes), and infrastructure as code with Terraform. •Machine Learning Expertise: Strong knowledge of machine learning algorithms, with experience adapting pre-trained and foundation models to domain-specific problems. •Large-Scale Data Processing: Experience with distributed computing frameworks such as Spark, and with lakehouse architectures on Databricks or equivalent, including Delta and Unity Catalog for data and model governance. •Data Engineering Skills: Solid understanding of data engineering principles, including data pipelines and ETL processes. •Problem-Solving Ability: Exceptional problem-solving skills with the capacity to tackle complex technical challenges. •Effective Communication: Excellent communication skills to effectively collaborate with cross-functional teams and convey technical concepts to non-technical stakeholders. •When You Join Our Team Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!