20 hours ago
Toronto, CanadaSenior
Responsibilities
- Design, develop, deploy, monitor, and manage end-to-end AI/ML solutions.
- Build scalable cloud-native AI/ML applications and services using AWS technologies.
- Develop and maintain data engineering, machine learning, and MLOps pipelines for batch and real-time workloads.
- Design Generative AI solutions using LLMs, Advanced RAG, vector databases, knowledge retrieval systems, agentic AI frameworks, and fine-tuning techniques.
- Design and implement knowledge graphs, graph databases, and relationship-based analytics.
- Translate business challenges into scalable analytical and AI-driven solutions with stakeholders and product teams.
- Conduct data discovery, exploratory analysis, data lineage work, root cause analysis, and data quality assessments.
- Implement model monitoring, observability, alerting, and operational support for production AI/ML solutions.
- Support enterprise AI governance, security, Responsible AI, privacy, and model risk management standards.
- Lead technical design discussions, serve as an AI/ML subject matter expert, and mentor team members.
- Evaluate emerging AI technologies and their applicability to business opportunities.
Requirements
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field; a master's degree is preferred.
- At least 6 years of experience in Machine Learning Engineering, Data Engineering, Software Engineering, or a related discipline.
- At least 3 years of hands-on experience building scalable data pipelines and ETL solutions using AWS services.
- Strong proficiency in Python and modern software engineering practices.
- Experience deploying and supporting production-grade AI/ML applications in cloud environments, preferably AWS.
- Strong experience with SageMaker, MLOps, model deployment, monitoring, and Machine Learning Development Lifecycle practices.
- Experience with Docker, ECS, and Kubernetes.
- Experience with Generative AI technologies including LLMs, Advanced RAG, vector databases, semantic search, agentic AI frameworks, and enterprise knowledge retrieval systems.
- Experience designing and implementing knowledge graph solutions and graph databases.
- Strong understanding of software engineering fundamentals, including system design, testing, security, observability, and version control.
- Ability to lead technical initiatives, influence architectural decisions, and collaborate across business and technology teams.
- Preferred experience with Kafka, Flink, or Kinesis for real-time data processing and streaming.
- Preferred experience with AI governance, Responsible AI, model risk management, enterprise-scale AI platform development, and solution architecture.
Benefits
- Hybrid working model designed to support flexibility, in-person learning, collaboration, and connection.
Tech Stack
Categories
About Vanguard
Vanguard is an investment management company offering low-cost index and active mutual funds, ETFs, brokerage, retirement plans, and financial advice for individual, institutional, and advisor clients. Founded in 1975 by John C. Bogle and headquartered in Valley Forge, PA, it operates a client-owned structure in which its funds own the firm. Its business model centers on asset-based management and advisory fees.