AI/ML Engineer

Socket.dev; Toronto; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

Vanguard's Corporate Services division seeks a Machine Learning/AI Engineer to design, build, and scale enterprise AI/ML solutions. The role focuses on production-grade AI, Generative AI, and analytics in a cloud-first environment.

You will partner with stakeholders and engineers to translate business problems into scalable AI-driven solutions, while ensuring data quality and governance across pipelines and deployments.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related field; Master preferred.
• 6+ years in Machine Learning Engineering, Data Engineering, Software Engineering, or related discipline.
• 3+ years building scalable data pipelines and ETL with AWS.
• Strong Python and modern software engineering practices.
• Experience deploying production AI/ML in cloud envs, preferably AWS.
• Experience with SageMaker, MLOps, CI/CD, MDLC; deployment and monitoring.
• Experience with containers and orchestration (Docker, ECS, Kubernetes).
• Experience with Generative AI tech including LLMs, RAG, vector DBs, knowledge retrieval.

Responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions with data ingestion and model lifecycle management.
• Build cloud-native AI/ML apps using AWS SageMaker, ECS, Lambda, S3, EventBridge, Step Functions.
• Develop data engineering and MLOps pipelines for batch and real-time workloads.
• Implement Generative AI using LLMs, RAG, vector databases, and enterprise knowledge retrieval systems.
• Design knowledge graphs and graph databases to enhance enterprise intelligence.
• Collaborate with stakeholders to translate business challenges into AI-driven solutions.
• Conduct data discovery, establish data lineage, and perform root cause analysis.
• Implement model monitoring, observability, and production support processes.
• Ensure governance, security, Responsible AI, privacy, and model risk management.
• Lead technical discussions and mentor team members on AI/ML best practices.
• Stay current on emerging AI tech and assess business applicability.

Skills

Python

Cloud computing

ML engineering

Data pipelines

CI/CD

Model deployment

Observability

Education

Bachelor's degree in CS/Engineering/Data Science

Master's degree preferred

Tools

SageMaker

Docker

ECS

Kubernetes

AWS

Job description

At Vanguard's Corporate Services division, we are seeking a Machine Learning/ AI Engineer to design, build, and scale enterprise AI/ML solutions that drive business innovation and support the development, deployment, and operationalization of intelligent applications. The ideal candidate combines strong software engineering, machine learning, and cloud expertise with hands‑on experience delivering production‑grade AI solutions. This role will partner closely with business stakeholders, product teams, and engineers to solve complex business problems using machine learning, Generative AI, and advanced analytics.

Responsibilities

• Design, develop, and deploy end‑to‑end AI/ML solutions, including data ingestion, feature engineering, model training, deployment, monitoring, and lifecycle management.

• Build scalable, cloud‑native AI/ML applications and services using AWS technologies such as SageMaker, ECS, Lambda, S3, EventBridge, and Step Functions.

• Develop and maintain machine learning, data engineering, and MLOps pipelines supporting batch and real‑time workloads.

• Design and implement Generative AI solutions leveraging Large Language Models (LLMs), Advanced RAG, vector databases, knowledge retrieval systems, agentic AI frameworks, and fine‑tuning techniques.

• Design and utilize knowledge graphs, graph databases, and relationship‑based analytics to enhance enterprise intelligence and decision‑making.

• Partner with business stakeholders to translate business challenges into scalable analytical and AI‑driven solutions.

• Conduct data discovery and exploratory analysis, establish data lineage, and perform root cause analysis to ensure data quality and reliability.

• Implement model monitoring, observability, alerting, and operational support processes for production AI/ML solutions.

• Ensure adherence to enterprise AI governance, security, Responsible AI, privacy, and model risk management standards.

• Serve as a machine learning engineering subject matter expert, lead technical design discussions, and mentor team members on AI/ML best practices.

• Stay current on emerging AI technologies and evaluate their application to business opportunities.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field; Master's degree preferred.

• 6+ years of experience in Machine Learning Engineering, Data Engineering, Software Engineering, or a related discipline.

• 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, CI/CD pipelines, model deployment, monitoring, and Machine Learning Development Lifecycle (MDLC) practices.

• Experience with containerization and orchestration technologies such as 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 effectively across business and technology teams.

Preferred Experience

• Real‑time data processing and streaming technologies such as Kafka, Flink, or Kinesis.

• AI governance, Responsible AI, and model risk management frameworks.

• Enterprise‑scale AI platform development and solution architecture.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in‑person learning, collaboration, and connection. We believe our mission‑driven and highly collaborative culture is a critical enabler to support long‑term client outcomes and enrich the employee experience.