AI & ML Engineer

Job Title: AI & ML Engineer – Azure & AWS Cloud PlatformsLocation: Toronto / HybridJob SummaryWe are seeking a highly skilled hands-on AI & ML Engineer with deep technical expertise in designing, developing, and deploying machine learning solutions on Microsoft Azure and Amazon Web Services (AWS). The ideal candidate will be highly technical, with proven experience in AWS Cloud Development Kit (CDK), modern MLOps practices, and production-grade AI/ML solution delivery.Key ResponsibilitiesAI/ML Solution Design & DevelopmentDesign, develop, and optimize machine learning and AI models (supervised, unsupervised, and deep learning).Perform data preprocessing, feature engineering, and exploratory data analysis (EDA).Select and implement appropriate algorithms, frameworks, and architectures to meet performance and scalability needs.Ensure reproducibility, performance tuning, and operational readiness of ML models.Cloud Architecture & IntegrationArchitect scalable, secure AI/ML solutions using:Azure: Machine Learning, Cognitive Services, Databricks, SynapseAWS: SageMaker, Rekognition, Comprehend, BedrockHands-on experience with AWS CDK is mandatory — design, build, and manage infrastructure-as-code for ML pipelines and applications.Integrate AI/ML workloads with data lakes, APIs, and event-driven architectures.Ensure cloud solutions comply with best practices for scalability, cost optimization, and security.MLOps & AutomationImplement and maintain CI/CD pipelines for ML lifecycle management (training, testing, and deployment).Use Azure DevOps, GitHub Actions, AWS CodePipeline, and AWS CDK/Terraform/CloudFormation for automation.Automate model deployment and monitoring processes.Continuously monitor model drift and performance; retrain and redeploy models as needed.Collaboration & Stakeholder EngagementWork closely with data engineers, data scientists, DevOps engineers, and architects to ensure end-to-end delivery of AI/ML solutions.Communicate complex AI/ML concepts clearly to both technical and non-technical stakeholders.Security, Compliance & GovernanceImplement data privacy, security, and compliance controls (HIPAA, GDPR, SOC 2).Apply Responsible AI principles for transparency, fairness, and explainability.Required Skills & QualificationsBachelor’s or Master’s degree in Computer Science, Data Science, or related field.5+ years of hands-on experience in AI/ML solution design, development, and deployment.3+ years of experience working across Azure and AWS AI/ML services.Mandatory: Strong hands-on experience with AWS CDK for infrastructure and automation.Proficiency in Python, R, and ML frameworks such as TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers.Experience with containerization and orchestration (Docker, Kubernetes – AKS/EKS).Familiarity with big data frameworks (Spark, Databricks) and cloud-native data tools (Azure Data Lake, AWS S3, Synapse, Redshift, Kinesis, Event Hubs).Preferred / Nice-to-HaveCertifications:Microsoft Certified: Azure AI Engineer Associate / Azure Solutions Architect ExpertAWS Certified Machine Learning – Specialty / AWS Solutions Architect – ProfessionalExposure to Generative AI, LLMs (OpenAI, Azure OpenAI, Amazon Bedrock).Knowledge of Edge AI and real-time inference deployment.Soft SkillsStrong analytical thinking, problem-solving, and technical ownership abilities.Excellent communication and collaboration skills.Proven ability to deliver high-quality solutions in a fast-paced, cross-functional environment.