MLOps Engineer
Job Summary
To support a growing team, the full-time remote MLOps Engineer will automate model training, testing, deployment, and monitoring workflows while collaborating with Data Engineers and DevOps teams to operationalize ML solutions.
Key responsibilities
- Implement model versioning, experiment tracking, and model registry solutions
- Monitor model performance, drift, and operational health in production environments
- Establish governance, security, access control, and auditability processes for ML platforms
Required qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
- Strong Python programming skills with experience in ML lifecycle management and deployment automation
- Hands-on expertise with tools such as MLflow, Kubeflow, and Amazon SageMaker
- Knowledge of Docker, Kubernetes, and CI/CD tools
- Experience taking ML/AI solutions from Proof of Concept (PoC) to Production
Complete Job Description
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