AI & ML Engineer

Job Title: AI & ML Engineer – Azure & AWS Cloud Platforms Location: Toronto / Hybrid Job Summary We 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 Responsibilities AI/ML Solution Design & Development Design, 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 & Integration Architect scalable, secure AI/ML solutions using: Azure : Machine Learning, Cognitive Services, Databricks, Synapse AWS : SageMaker, Rekognition, Comprehend, Bedrock Hands-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 & Automation Implement 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 Engagement Work 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 & Governance Implement data privacy, security, and compliance controls (HIPAA, GDPR, SOC 2). Apply Responsible AI principles for transparency, fairness, and explainability. Required Skills & Qualifications Bachelor’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-Have Certifications: Microsoft Certified: Azure AI Engineer Associate / Azure Solutions Architect Expert AWS Certified Machine Learning – Specialty / AWS Solutions Architect – Professional Exposure to Generative AI, LLMs (OpenAI, Azure OpenAI, Amazon Bedrock). Knowledge of Edge AI and real-time inference deployment. Soft Skills Strong 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.