Machine Learning Operations Engineer

Position Description

We are seeking an experienced MLOps Engineer with strong expertise in Python and big data technologies to join our team. This role focuses on operational excellence, including optimizing feature engineering pipelines and maintaining machine learning models in production environments. The candidate will work closely with platform and data science teams to ensure scalable, reliable, and high-performance ML workflows using existing frameworks.

• Optimize and maintain large-scale feature engineering pipelines using PySpark, Pandas, and PyArrow on Hadoop-based infrastructure.
• Refactor and modularize ML codebases to enhance reusability, maintainability, and performance.
• Collaborate with platform teams on compute capacity planning, resource allocation, and system upgrades.
• Integrate with existing model serving frameworks to support testing, deployment, and rollback processes.
• Monitor and troubleshoot production ML pipelines, ensuring high reliability, low latency, and cost efficiency.
• Contribute to internal ML platforms by sharing insights, proposing improvements, and documenting best practices.
• Build near real‑time ML pipelines using Kafka and Spark Streaming.
• Work with AWS and Sage Maker MLOps ecosystem.

• 6+ years of experience in software engineering, data engineering, or MLOps roles.
• Strong programming expertise in Python, with hands‑on experience in Pandas, PySpark, and PyArrow.
• Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.
• Experience with CI/CD pipelines and best practices in ML environments.
• Hands‑on experience with monitoring tools for ML pipeline health and performance.
• Strong collaboration skills with experience working in cross‑functional teams (platform, data science, engineering).
• Experience contributing to or building internal MLOps frameworks/platforms.
• Familiarity with SLURM clusters or other distributed job schedulers.
• Exposure to Kafka, Spark Streaming, or other real‑time data processing technologies.
• Understanding of ML lifecycle management, including versioning, deployment, and drift detection.

CGI’s estimated compensation range for this role in the U.S. is $62,900.00 – $.

• Competitive compensation
• Comprehensive insurance options
• Matching contributions through the 401(k) plan and the share purchase plan
• Paid time off for vacation, holidays, and sick time
• Paid parental leave
• Learning opportunities and tuition assistance
• Wellness and Well‑being programs

Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.

CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_ and reference the Position  the position in which you are interested.