Description

About the Company:

Founded in 1976, CGI is one of the largest independent IT and business consulting services firms in the world. With 94,000 professionals across the globe and FY2024 revenue of CA$14.68 billion, CGI delivers a wide range of strategic consulting, system integration, and IP services. Through its global delivery network and local relationship model, CGI helps clients transform their organizations digitally.

About the Role:

CGI is seeking an experienced MLOps Data Engineer to support machine learning model development and deployment using modern data engineering technologies and workflows. The role will involve developing data pipelines, managing ML infrastructure, and ensuring reliable and scalable deployments of ML models.

Responsibilities:

• Design, develop, and maintain data pipelines for ML models using Hadoop, PySpark/Scala, and cloud platforms.
• Handle data wrangling and preparation for data science, analytics, or reporting.
• Work on Spark Structured Streaming for near-real-time data processing.
• Implement CI/CD pipelines using Jenkins for ML workflows.
• Deploy and manage Docker/Kubernetes environments for containerized ML services.
• Utilize MLOps tools such as Kubeflow and MLflow for model versioning and deployment.
• Implement and manage Hopsworks Feature Store and Cloudera CDP environment.
• Perform automated testing, data model management, and monitoring of deployed ML models.
• Collaborate with cross-functional teams and document project status.
• Maintain strong customer orientation and manage project timelines.

Key Technical Skills:

Data Analysis, Hadoop Hive, Python

Requirements:

• 5–8 years of experience in software/data engineering with ML focus.
• Bachelor’s degree in Computer Science or related field.
• Proficiency in Python, SQL, Java/Scala, and data technologies.
• Hands-on experience in cloud platforms (AWS/GCP/Azure).
• Prior exposure to CI/CD, containerization, and real-time data processing.
• Experience in machine learning pipelines, versioning, and automated deployment.
• Excellent communication and teamwork skills.

Preferred Qualifications:

• Knowledge of IBM Mainframe – CA7 Scheduler, DOC05, DOC40, AGENT.
• Certification or training in MLOps frameworks or cloud environments is a plus.