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AI & ML Engineer with strong experience building and deploying cloud-native ML solutions across Azure and AWS. This role requires deep technical expertise, production-level engineering skills, and mandatory hands-on experience with AWS CDK.
Key Responsibilities:
- Design and develop ML/AI models (supervised, unsupervised, deep learning).
- Build scalable AI/ML architectures using Azure ML, Cognitive Services, Databricks, AWS SageMaker, Rekognition, Comprehend, etc.
- Develop and automate end-to-end MLOps pipelines using Azure DevOps, GitHub Actions, AWS CodePipeline.
- Deploy cloud-native ML workloads using Docker, Kubernetes (AKS/EKS).
- Integrate ML pipelines with data lakes, warehouses, and APIs.
- Ensure architecture follows best practices for security, reliability, and compliance.
Required Skills:
- 5+ years in AI/ML engineering (model development, deployment).
- 3+ years hands-on with Azure + AWS ML services.
- Mandatory hands-on AWS CDK experience.
- Strong Python, ML frameworks (TensorFlow, PyTorch, scikit-learn).
- Experience with Spark/Databricks, CI/CD, IaC (Terraform/CloudFormation).
- Expertise in containerization and orchestration (Docker, AKS/EKS).
Key Skills
Ranked by relevance
aws
docker
cloud
technical expertise
containerization
kubernetes
tensorflow
aws cdk
pytorch
python
devops
mlops
cicd
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- Posted
- Dec 10, 2025
- Type
- Contract
- Level
- Mid-Senior
- Location
- Greater Toronto Area
- Company
- KTek Resourcing
Industries
IT Services
IT Consulting
Categories
Information Technology
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