AI/ML Engineer

VDart Inc; Toronto; On-site; CAD 100,000 - 130,000; Full time

Job summary

A technology solutions provider is seeking an AI / ML Engineer in Toronto to design and deploy machine learning solutions using Azure and AWS. The role requires strong proficiency in Python and cloud-native services, emphasizing collaboration with cross-functional teams. Ideal candidates will have substantial experience in AI / ML solution deployment. This is a hybrid position with contract duration of 6 months.

Qualifications

• 5 years of experience in AI / ML solution development and deployment.
• 3 years of hands-on experience in Azure and AWS AI / ML services.
• Strong understanding of cloud-native data storage and processing.

Responsibilities

• Design, develop, and optimize machine learning and AI models.
• Architect scalable AI / ML solutions using Azure and AWS services.
• Implement and maintain CI / CD pipelines for ML models.

Skills

Machine learning and AI model development

Cloud-native AI / ML services

Data preprocessing

Python programming

Containerization with Docker

Education

Bachelor's or Master’s degree in a relevant field

Tools

Azure Machine Learning

AWS SageMaker

TensorFlow

PyTorch

Docker

Kubernetes

Job description

Overview

Title: AI / ML Engineer

Location: Hybrid - Toronto

Duration: Contract 6 Months

Job Summary :

We are seeking a highly skilled AI & ML professional with deep expertise in designing developing and deploying machine learning solutions on Microsoft Azure and Amazon Web Services (AWS). The ideal candidate will have strong hands-on experience with cloud-native AI / ML services modern data engineering practices MLOps pipelines and production-scale deployment strategies.

AI / ML Solution Design & Development

• Design, develop and optimize machine learning and AI models including supervised, unsupervised and deep learning approaches.
• Select appropriate algorithms and frameworks based on business use cases and performance requirements.
• Conduct data preprocessing, feature engineering and exploratory data analysis.

Cloud Architecture & Integration

• Architect scalable AI / ML solutions using Azure Machine Learning, Azure Cognitive Services, Azure Databricks, AWS SageMaker, AWS Rekognition, AWS Comprehend and related services.
• Integrate AI / ML pipelines with data lakes, data warehouses and APIs.
• Ensure solutions adhere to cloud architecture best practices, security and compliance standards.

MLOps & Automation

• Implement and maintain CI / CD pipelines for ML model training, testing and deployment.
• Leverage Azure DevOps, GitHub Actions, AWS CodePipeline and Terraform / CloudFormation for automation.
• Monitor model performance and retrain models as needed.

Collaboration & Stakeholder Engagement

• Work closely with data engineers, data scientists, DevOps engineers and product managers to align AI / ML solutions with business goals.
• Present solution designs, performance metrics and recommendations to technical and non-technical stakeholders.

Security Compliance & Governance

• Implement data privacy and compliance measures (e.g. HIPAA, GDPR, SOC 2).
• Apply responsible AI principles for fairness, transparency and explainability.

Required Skills & Qualifications

• Bachelor's or Master’s degree in Computer Science, Data Science, AI / ML or a related field.
• 5 years of experience in AI / ML solution development and deployment.
• 3 years of hands-on experience in Azure and AWS AI / ML services.
• Proficiency in Python, R and relevant ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers).
• Strong understanding of cloud-native data storage, processing and streaming (Azure Data Lake, AWS S3, Azure Synapse, AWS Redshift, Kinesis, Event Hubs).
• Experience with Docker, Kubernetes (AKS / EKS) for containerized ML workloads.
• Familiarity with big data frameworks (Spark, Databricks).