Senior AI/ML Developer

CGI•Reston, VA

2d•Hybrid

About The Position

Our client is seeking a Senior AI/ML Developer to support enterprise-scale machine learning initiatives within a highly collaborative AWS-based environment. This role will focus on designing, maintaining, and optimizing end-to-end ML workflows across Domino and Amazon SageMaker platforms. The ideal candidate will have strong experience in machine learning engineering, MLOps, and scalable data pipeline development, with a solid understanding of model governance, explainability, and operational best practices. The engineer will work closely with data scientists, platform engineers, and governance teams to ensure models are production-ready, traceable, and compliant with enterprise standards. This is a hybrid opportunity based in Reston, VA, requiring onsite presence three days per week.

Requirements

5+ years of hands-on experience working in AWS-centric machine learning environments
Deep understanding of Amazon SageMaker and ML platform operations
Experience using Domino Data Lab or similar enterprise ML platforms
Advanced Python programming skills for ML engineering and automation
Practical experience implementing MLflow for experiment tracking and model lineage
Ability to design and maintain scalable data pipelines for training and inference workloads
Knowledge of feature engineering techniques and data preparation best practices
Experience with model validation, explainability, fairness, and bias testing frameworks
Familiarity with model packaging, deployment processes, and lifecycle management
Strong understanding of MLOps principles, CI/CD workflows, and version control practices
Experience collaborating with cross-functional teams including data science, engineering, and governance stakeholders
Ability to troubleshoot production ML issues and improve operational efficiency
Bachelor's degree in Computer Science, Information Systems, or a related field.

Nice To Haves

AWS certifications such as AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect are a plus

Responsibilities

Designing, maintaining, and optimizing end-to-end ML workflows across Domino and Amazon SageMaker platforms.
Working closely with data scientists, platform engineers, and governance teams to ensure models are production-ready, traceable, and compliant with enterprise standards.
Implementing MLflow for experiment tracking and model lineage.
Designing and maintaining scalable data pipelines for training and inference workloads.
Implementing ML model validation, explainability, fairness, and bias testing frameworks.
Managing model packaging, deployment processes, and lifecycle management.
Applying MLOps principles, CI/CD workflows, and version control practices.
Collaborating with cross-functional teams including data science, engineering, and governance stakeholders.
Troubleshooting production ML issues and improving operational efficiency.