MLOps Engineer

Job Description

Position Title:

MLOps Engineer

Job Location:

Cario / Remote

Job type:

Full‑time

Summary:

We are seeking an MLOps Engineer who bridges the gap between data science and production systems. You’ll be responsible for deploying, monitoring, and automating machine learning models in production environments, ensuring they operate reliably and efficiently.

Key Responsibilities:

  • Build, deploy, and scale ML pipelines using tools like Kubeflow, MLflow, or SageMaker

  • Automate model training, validation, and retraining workflows

  • Monitor model performance, detect drift, and trigger retraining as needed

  • Work with data scientists to productionize ML models and integrate them into applications

  • Ensure model governance, version control, and reproducibility

  • Implement infrastructure (containers, cloud services) to support scalable ML workloads

Skills & Qualifications:

  • Bachelor’s degree in Computer Science, Machine Learning, or related field

  • Experience with cloud ML solutions (AWS SageMaker, GCP AI Platform, or Azure ML)

  • Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn)

  • Knowledge of container orchestration (Kubernetes) and CI/CD for ML

  • Understanding of data engineering and production-level software development

apply for this position

if you do not hear back within 3-5 days of submitting your application please note that you have been unsuccessfull at this time.