Senior AWS Full Stack ML Engineer

Senior AWS Full Stack ML Engineer

Category:
Software Development/ Engineering

Main location:
United States, Virginia, Reston

Position : J

Employment Type:

Full Time

U.S.

- Finding purpose at CGI ()

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CGI has an immediate need for a Senior AWS Full Stack ML Engineer to join our team. This is an exciting opportunity to work in a fast-paced team environment supporting one of the largest customers. We take an innovative approach to supporting our client, working side‑by‑side in an agile environment using emerging technologies.

We partner with 15 of the top 20 banks globally, and our top 10 banking clients have worked with us for an average of 26 years!.

This role is located at a client site in Reston, VA. A hybrid working model is acceptable.

We are seeking a highly experienced AWS Full Stack ML Engineer to operationalize and optimize large-scale financial modeling platforms. This role blends machine learning expertise, full‑stack software engineering, and deep AWS cloud knowledge, with a strong emphasis on building scalable and secure MLOps ecosystems.

The ideal candidate will bridge the gap between data science experimentation and enterprise‑grade production systems. You will transform model prototypes into resilient, compliant, and high‑performance solutions while ensuring reliability, observability, and cost efficiency in a regulated financial environment.

This position requires hands‑on ownership of ML pipelines, infrastructure automation, cloud architecture, and cross‑functional collaboration to deliver secure and scalable AI‑driven applications.

• 6+ years of experience in MLOps, Dev Ops, or ML engineering
• Proven experience designing and maintaining end‑to‑end MLOps pipelines
• Hands‑on experience with CI/CD tools (Git Lab, Jenkins, AWS Code Pipeline)
• Experience with workflow orchestration tools such as AWS Step Functions or Apache Airflow
• Strong proficiency in Python
• Experience with ML frameworks such as Tensor Flow, PyTorch, Scikit‑learn
• Ability to refactor and product ionize data science code
• Solid understanding of model performance monitoring and data drift detection
• Deep experience with AWS services, including Amazon Sage Maker, S3, EC2, EKS / ECS / Fargate, Lambda, AWS Glue, IAM
• Experience implementing Infrastructure as Code using Terraform or AWS Cloud Formation
• Strong knowledge of secure AWS architectures (IAM roles, VPC configurations, encryption best practices)
• Experience optimizing AWS environments for performance, availability, and cost efficiency
• Experience designing scalable ETL pipelines and data workflows
• Ensuring data quality and availability for training and inference at scale
• Monitoring and alerting using tools such as Amazon Cloud Watch
• Strong understanding of microservices architecture and system design
• Familiarity with containerization (Docker) and orchestration (ECS/EKS)
• Experience with Git‑based version control and code quality practices
• Knowledge of testing frameworks and debugging methodologies
• Strong problem‑solving and troubleshooting skills
• Ability to work cross‑functionally with data scientists, engineers, and business stakeholders
• Clear communicator who can translate complex ML infrastructure topics into practical solutions
• Preferred:
  Experience in financial modeling environments or regulated industries
• AWS Certified Machine Learning – Specialty
• AWS Certified Solutions Architect – Associate
• Other relevant cloud or ML certifications

Bachelor's degree in Computer Science, Information Systems, or a related field.

A reasonable estimate of the current range for this role in the U.S. is $ - $.

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

• Dev Ops
• ETL
• Jenkins
• Terraform

Together, as…