onsite
MLOps Engineer - Coffee Beans
MLOps Engineer
Senior MLOps Engineer responsible for designing, automating, and maintaining end‑to‑end machine learning pipelines, containerizing services, and ensuring robust model monitoring and version control in a production environment.
About the role
Key Responsibilities
- Design and develop scalable MLOps pipelines for model deployment and integration.
- Collaborate with data scientists and senior engineers to operationalize machine learning models.
- Automate model training, testing, and deployment workflows using Python and shell scripting.
- Monitor production models, detect performance anomalies, and coordinate remediation.
- Implement and maintain version control practices for models and data using Git.
- Containerize ML services with Docker and orchestrate deployments.
- Set up and maintain Jenkins pipelines for continuous integration and delivery.
Requirements
- 5–7 years of experience in MLOps or related roles.
- Experience with Git and CI/CD best practices.
- Excellent problem‑solving skills and ability to work in a fast‑paced environment.
Skills
pythondockerjenkins