onsite
Machine Learning Engineer / MLOps Engineer - CGI Technologies and Solutions, Inc.
MLOps Engineer
Design, develop, and operationalize machine‑learning models using Python, cloud services, and container orchestration to deliver scalable AI solutions.
About the role
Key Responsibilities
- Develop, train, and fine‑tune machine‑learning models using frameworks such as TensorFlow or PyTorch.
- Build end‑to‑end MLOps pipelines that automate data ingestion, model training, validation, and deployment.
- Containerize models and services with Docker and orchestrate them on Kubernetes clusters.
- Implement CI/CD workflows for model versioning, testing, and continuous delivery.
- Monitor model performance in production, troubleshoot issues, and iterate to improve accuracy and latency.
- Collaborate with data engineers, software developers, and product owners to integrate AI capabilities into business applications.
Requirements
- Strong proficiency in Python and experience with machine‑learning libraries (TensorFlow, PyTorch, scikit‑learn).
- Hands‑on experience building and maintaining MLOps pipelines, including data preprocessing, model registry, and automated deployment.
- Solid understanding of container technologies (Docker) and orchestration platforms (Kubernetes) in cloud environments.
- Familiarity with cloud services (AWS, GCP, or Azure) and infrastructure‑as‑code tools.
- Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and version control (Git).
Skills
pythontensorflowpytorchdockerkubernetesawscicdmlops