Python + ML + MLOps

Python + Machine Learning + MLOps Engineer

We are seeking a skilled Python + Machine Learning + MLOps Engineer to design, build, and deploy scalable machine learning solutions across enterprise environments. You will develop end-to-end ML pipelines, operationalize models in production, and collaborate with cross-functional teams to deliver reliable, high-performance AI solutions.

• Design, develop, and deploy machine learning models and data-driven solutions using Python.
• Build and maintain end-to-end ML pipelines for data ingestion, training, validation, deployment, and monitoring.
• Develop scalable and production-ready machine learning systems following MLOps best practices.
• Optimize model performance, reliability, and scalability across cloud and on-premise environments.
• Collaborate with data scientists, data engineers, and business stakeholders to translate requirements into ML solutions.
• Implement automated model training, testing, deployment, and monitoring workflows.
• Establish CI/CD pipelines for machine learning applications and model lifecycle management.
• Monitor model drift, data quality, and production performance to ensure continuous improvement.
• Contribute to code reviews, technical documentation, and engineering best practices.
• Strong Python programming skills with hands-on experience in machine learning development.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar.
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, Airflow, DVC, or SageMaker.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.

Good to Have

• Experience with cloud platforms including Azure, AWS, or Google Cloud Platform.
• Knowledge of DevOps practices, Infrastructure as Code (Terraform, Ansible), and CI/CD tools.
• Exposure to Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Experience with big data technologies such as Spark, Hadoop, or Databricks.
• Understanding of model governance, responsible AI practices, and ML security.

Naukri Mapping

• Department: Engineering - Software & QA
• Role Category: Data Science & Machine Learning
• Role: Machine Learning Engineer / MLOps Engineer / Senior ML Engineer