MLOps and Kubernetes define this DevOps Specialist chance at MDA Space, building reliable infrastructure for machine learning development and production.
As a DevOps Specialist, you will bridge machine learning development with production engineering for Geointelligence systems. You will design, build, and maintain tooling that helps AI and ML Analysts and Engineers deploy, monitor, and iterate models. The work spans Python, Docker, Terraform, AWS, and Kubernetes.
Key Responsibilities: Design scalable MLOps platforms for on-premise and AWS environments
Build reusable infrastructure-as-code modules for ingestion and model serving
Automate model pipelines, versioning, lineage, and metadata tracking
Create observability, alerts, and self-healing mechanisms for live models




Support secure access, encryption, audits, and risk assessments
Requirements: Degree in Computer Science, Engineering, Data Science, or related field
Three-plus software development years, including two MLOps years
Python and one compiled language such as C++, Go, or Rust
Docker, Kubernetes, Terraform, Ansible, and CI/CD/CT proficiency
AWS, model serving, tracking, monitoring, and observability experience
Build MLOps platforms, production pipelines, and secure AI systems as part of MDA Space’s Geointelligence team.

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📌 MLOps DevOps Specialist (British Columbia)
🏢 MDA
📍 British Columbia