ML OPS Engineer

Job Description

Job Description

Overview

CTG is seeking to fill a ML OPS Engineer position for our client in Phoenix, AZ.

Duration : 12 months

Duties :

Build, deploy, and maintain robust machine learning pipelines and production workflows.

Collaborate with data science and engineering teams to operationalize ML models at scale.

Monitor, troubleshoot, and optimize model performance in real-time production environments.

Implement automated CI / CD pipelines for ML workflows and ensure reproducibility across experiments.

Manage version control for code, datasets, and model artifacts.

Apply DevOps best practices to ML systems, ensuring reliability, security, and scalability.

Skills :

Expert in Python for ML, data processing, and scripting.

Proficient with Git version control (GitHub, GitLab, BitBucket, SVN).

Solid understanding of ML model lifecycle, deployment, and monitoring.

Experience with containerization, orchestration (Docker, Kubernetes), and cloud platforms is a plus.

Strong problem-solving and automation mindset.

Experience :

Proven experience deploying and maintaining ML models in production environments.

Hands-on experience with ML pipelines, CI / CD for ML, and collaboration in cross-functional teams.

Education :

Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience).

Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required.

CTG does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services for this role.

To Apply :

To be considered, please apply directly to this requisition using the link provided. For additional information, please contact JoAnn Abramo at JoAnn.Abramo@ctg.com . Kindly forward this to any other interested parties. Thank you!