We are looking for a skilled MLOps Engineer to help design, deploy, automate, and manage scalable machine learning pipelines in production environments.

If you have hands-on experience in Python, ML frameworks, cloud platforms, and ML lifecycle automation, this is an excellent chance to contribute to enterprise-level machine learning solutions in a flexible, remote working environment.

? Role: MLOPS Engineer

? Job Type: Part-Time | Remote | Freelance

Key Responsibilities:

- Design and implement end-to-end machine learning pipelines, from data ingestion to model deployment.
- Build and maintain CI/CD pipelines for ML model training, testing, validation, and deployment.
- Automate model monitoring, retraining, performance tracking, and optimization.
- Collaborate with Data Scientists and Data Engineers to productionize machine learning models.
- Ensure scalability, reliability, security, and reproducibility of ML systems.




- Manage model versioning, experiment tracking, and ML lifecycle management.
- Implement governance, compliance, and best practices for production ML environments.

Required Skills & Expertise:

- Strong programming skills in Python.
- Experience with TensorFlow, PyTorch, and Scikit-learn.
- Hands-on experience with MLOps tools such as MLflow, Kubeflow, Airflow, AWS SageMaker, or Azure ML.
- Knowledge of CI/CD tools such as Jenkins, GitHub Actions, and GitLab CI.
- Experience with AWS cloud services and ML deployment infrastructure.
- Solid understanding of data pipelines, ETL processes, and distributed systems.
- Experience with model monitoring, automated retraining, and production ML operations.

📌 Freelance MLOPS Engineer (India)
🏢 IndiTech Consulting
📍 India