Software Engineer ( Machine Learning Ops )
On-site · Bengaluru, Karnataka, India
Job Summary
Design, implement and maintain ML pipelines for model training, validation, and deployment. Automate model training, testing and deployment (CI/CD of ML models). Monitor model performance, data drift, and system health in production environments and deploy models in pre-prod and prod. Collaborate with data scientists to operationalize machine learning models and algorithms. Implement version control for models, datasets, and ML experiments using MLOps tools. Optimize ML infrastructure for scalability, reliability, and cost-effectiveness. Troubleshoot and resolve issues related to model deployment and production systems. Maintain documentation for ML workflows, deployment processes, and system architecture. This role may require availability outside of standard business hours as part of a rotational on-call schedule.
Required Qualifications
- 3 -5 years of experience in software development, DevOps, or data engineering
- Proficiency in Python, SQL, and at least one ML framework such as TensorFlow, PyTorch, Scikit-learn
- Experience with containerization (Docker) and orchestration tools (Kubernetes)
- Knowledge of cloud platforms such as AWS, Azure, GCP and their ML services
- Understanding of CI/CD pipelines, version control (Git), and infrastructure as code
- Familiarity with monitoring tools and logging frameworks for production systems
- Experience with data pipeline tools such as Apache Airflow, Kubeflow, or similar
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