Role overview
Greetings
We're seeking a hands-on MLOps Solution Architect to design and implement scalable, secure, and cost-effective ML platforms on AWS . You'll lead the end-to-end architecture for model training, CI/CD pipelines, deployment strategies, monitoring, and governance across teams of data scientists and engineers.
Location: Toronto, ON (Hybrid- 3 days onsite per week)
Client: One of the largest banks in Canada
Duration: Long-term contract
What we're looking for
Must-Have Skills • 14+ years of experience in ML/AI platform design and data infrastructure • Deep expertise in AWS services: • Compute: EC2, EKS, Batch, Lambda • Storage: S3, Lake Formation, Glue Catalog • Pipeline: Step Functions, CodePipeline, Airflow • Training/Serving: SageMaker (Studio, Training, Model Registry, Endpoints) • Monitoring: CloudWatch, CloudTrail, Prometheus • Security: IAM, Secrets Manager, KMS, VPC • Proficient in Python and infrastructure scripting (Terraform, CloudFormation) • Experience building and deploying models in production environments (CI/CD) • Familiar with data versioning (DVC, Delta Lake) and experiment tracking (MLflow) • Strong understanding of containerization (Docker, EKS) and Kubernetes-based serving • Excellent communication and stakeholder management
Best Regards,