Scheduled Hiring Drive MLOps Engineer - Pune

We are conducting a Scheduled Hiring Drive in Pune for experienced MLOps Engineers who are passionate about building scalable, reliable, and production-ready machine learning systems. Role: MLOps Engineer Experience: 4 16 Years Location: Pune Key Skills & Experience: Strong experience in Machine Learning Operations (MLOps), ML lifecycle management, and productionizing ML models.Hands-on experience building and maintaining end-to-end ML pipelines including data preparation, training, deployment, and monitoring.Experience with CI/CD automation, model versioning, experiment tracking, and reproducibility practices.Strong programming skills in Python and SQL.Experience with ML platforms such as Databricks, MLflow, and SageMaker.Good understanding of cloud platforms (AWS, Azure, or GCP) and DevOps practices.Experience with model monitoring, data drift detection, governance, and security controls.Familiarity with Docker, Kubernetes, feature stores, model governance, and automated retraining workflows is preferred.Strong problem-solving skills with the ability to optimize and support scalable ML systems. We are conducting a Scheduled Hiring Drive in Pune for experienced MLOps Engineers who are passionate about building scalable, reliable, and production-ready machine learning systems. Role: MLOps Engineer Experience: 4 16 Years Location: Pune Key Skills & Experience: Strong experience in Machine Learning Operations (MLOps), ML lifecycle management, and productionizing ML models.Hands-on experience building and maintaining end-to-end ML pipelines including data preparation, training, deployment, and monitoring.Experience with CI/CD automation, model versioning, experiment tracking, and reproducibility practices.Strong programming skills in Python and SQL.Experience with ML platforms such as Databricks, MLflow, and SageMaker.Good understanding of cloud platforms (AWS, Azure, or GCP) and DevOps practices.Experience with model monitoring, data drift detection, governance, and security controls.Familiarity with Docker, Kubernetes, feature stores, model governance, and automated retraining workflows is preferred.Strong problem-solving skills with the ability to optimize and support scalable ML systems.