Intermediate DevOps Engineer

About MDA Space

With over 55 years of pioneering achievements and more than 450 missions, MDA Space is a leading global partner in robotics, satellite systems, and geointelligence. The company is renowned for its expertise in communications satellites, Earth and space observation, and space exploration infrastructure. Employing over 4,000 experts worldwide, MDA Space combines deep engineering knowledge with a passion for innovation to turn ambitious customer visions into reality.

Role Overview

MDA Space seeks a DevOps Specialist skilled in MLOps to connect machine learning development with operational deployment. This position involves designing, building, and maintaining infrastructure and tooling that empower AI and ML teams to swiftly develop, deploy, and monitor machine learning models at scale. As a key contributor to the Geointelligence DevSecOps and MLOps team, you will integrate software engineering, DevOps, and machine learning to ensure systems are reliable, reproducible, and efficiently executed.

Key Responsibilities

• Design and enhance a secure, scalable MLOps platform incorporating components such as model registry, continuous integration/delivery/testing, feature stores, experiment tracking, and monitoring, leveraging Kubernetes and Terraform for both on-premise and AWS cloud environments.
• Create reusable infrastructure-as-code modules focused on data ingestion, model serving, and automatic scaling capabilities.
• Develop automated CI/CD pipelines to transition model code, data schemas, and container images from development to production with minimal downtime.
• Integrate model version control with comprehensive data lineage and metadata management.
• Construct observability tools to monitor latency, throughput, model drift, and resource use in production.
• Implement automated alerting and self-healing solutions for model anomalies and hardware issues.
• Collaborate with AI/ML analysts to convert research notebooks into production-grade pipelines, providing tools, best practice guidance, and code review support.
• Work with Corporate IT, technical governance, and platform teams to promote MLOps best practices and platform adoption.
• Ensure data security via encryption in transit and at rest, role-based access, and secure secret management compliant with government and industry standards.
• Participate in risk assessments and audit processes relating to Geointelligence AI and ML systems.
• Evaluate new technologies for potential adoption and contribute to open-source or internal reusable components.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related disciplines.
• Minimum three years of software development experience, including at least two years focusing on MLOps.
• Strong Python programming skills plus proficiency in at least one compiled language such as C, C++, Go, or Rust.
• Experience with Docker containerization and Kubernetes orchestration.
• Hands-on expertise in infrastructure as code tools such as Terraform and Ansible.
• Familiarity with CI/CD/CT tooling and model serving frameworks.
• Knowledge of experiment tracking and metadata management systems.
• Experience with monitoring and observability platforms.
• Proficient in AWS cloud services, especially EKS, storage solutions, and AI/ML tools like SageMaker or Bedrock.
• Excellent communication skills capable of explaining technical concepts to non-technical audiences.
• Ability to proactively resolve problems in a dynamic, mission-critical setting.

Additional Information

Candidates must be able to obtain and maintain security clearance at the reliability status level and pass the Controlled Goods Program (CGP) security assessment. MDA is committed to diversity, equity, and inclusion, providing accommodations in the hiring process upon request. The remuneration range for this role is $78,000 to $108,000 annually, based on qualifications and experience. Employees and their dependents have access to comprehensive benefits including extended health care, dental, vision, disability insurance, life insurance, retirement savings plans, and employee assistance programs.