Senior AI/ML Engineer — Generative AI & MLOps on AWS

The Vanguard Group; Toronto; Hybrid; CAD 160,000 - 220,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Vanguard is seeking an experienced ML Engineer to design, develop, and deploy end-to-end AI/ML solutions with a focus on data ingestion, feature engineering, model training, and deployment. You will build scalable, cloud-native apps using AWS SageMaker, Docker, and Kubernetes, while ensuring governance and risk management.

You will lead MLOps practices, collaborate with stakeholders, and mentor teammates, delivering reliable AI capabilities across batch and streaming workloads.

Qualifications

• Bachelors degree in a technical field; Masters preferred.
• 6+ years in ML Engineering, Data Engineering, Software Engineering, or related disciplines.
• 3+ years building scalable data pipelines and ETL with AWS services.
• Strong Python proficiency and modern software engineering practices.
• Production-grade AI/ML apps in cloud environments, preferably AWS.
• Experience with SageMaker, MLOps, CI/CD, model deployment, monitoring, and MDLC.
• Experience with containerization/orchestration (Docker, ECS, Kubernetes).
• Experience with Generative AI tech (LLMs, vector DBs, semantic search, enterprise retrieval).
• Knowledge graph design and graph databases.
• Strong system design, security, observability, and version control knowledge.
• Ability to lead initiatives and cross-team collaboration.

Responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions across the lifecycle.
• Build scalable, cloud-native AI/ML applications using AWS technologies.
• Develop and maintain ML, data, and MLOps pipelines for batch and real-time workloads.
• Design and implement Generative AI solutions with LLMs and RAG.
• Use knowledge graphs and graph databases to boost enterprise analytics.
• Collaborate with stakeholders to translate business challenges into scalable AI solutions.
• Perform data discovery, lineage, and root-cause analysis for data quality.
• Implement model monitoring, observability, and operational support for production AI/ML solutions.
• Ensure adherence to AI governance, privacy, and risk management standards.
• Mentor team members on AI/ML best practices and lead technical discussions.
• Stay current on emerging AI technologies and assess business applications.

Skills

Python

AWS SageMaker

MLOps

CI/CD

Docker

Kubernetes

Data pipelines

Education

Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related field

Tools

AWS

SageMaker

Docker

Kubernetes

Kafka/Kinesis

Job description

Vanguard is seeking an experienced ML Engineer to design, develop, and deploy end-to-end AI/ML solutions with a focus on data ingestion, feature engineering, model training, and deployment. You will build scalable, cloud-native apps using AWS SageMaker, Docker, and Kubernetes, while ensuring governance and risk management.

You will lead MLOps practices, collaborate with stakeholders, and mentor teammates, delivering reliable AI capabilities across batch and streaming workloads.