MLOps Engineer

About the Role

<h2>MLOps Engineer</h2><p>We are seeking a skilled MLOps Engineer with 5?8 years of experience in building, deploying, automating, and monitoring machine learning solutions in production environments. The ideal candidate will have expertise in CI/CD pipelines, cloud infrastructure, containerization, model deployment, and monitoring frameworks to ensure secure, scalable, and reliable AI/ML operations. The candidate will collaborate closely with Data Scientists, DevOps Engineers, Cloud Teams, and Business Stakeholders to operationalize machine learning models efficiently.</p><h3>Key Responsibilities</h3><ul><li>Design and implement scalable MLOps pipelines for model training, testing, deployment, and monitoring.</li><li>Automate CI/CD workflows for machine learning applications.</li><li>Manage model versioning, deployment automation, and rollback strategies.</li><li>Build monitoring and alerting systems for model performance and data drift.</li><li>Work with cloud-native AI/ML platforms and container orchestration tools.</li><li>Collaborate with Data Science teams to productionize ML models.</li><li>Ensure security, governance, compliance, and reliability of AI systems.</li><li>Optimize infrastructure for performance, scalability, and cost efficiency.</li><li>Maintain documentation and operational standards for ML workflows.</li></ul><h3>Requirements</h3><ul><li><strong>Mandatory Skills:</strong> Strong hands-on experience in Python, Linux, SQL, Shell Scripting.</li><li>Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI/CD), Docker, Kubernetes.</li><li>Knowledge of ML model deployment, model monitoring, API deployment.</li><li>Cloud platform experience: AWS / Azure / GCP.</li><li>Experience with MLflow, Airflow, Terraform.</li><li>Understanding of DevOps and Infrastructure as Code (IaC).</li><li>Strong troubleshooting and automation skills.</li></ul><ul><li><strong>Preferred Skills:</strong> Experience with Kubeflow, SageMaker, Azure ML, Vertex AI.</li><li>Knowledge of data drift and model drift monitoring, observability tools (Prometheus, Grafana).</li><li>Exposure to generative AI deployment, LLMOps, feature stores.</li><li>Familiarity with Spark/PySpark.</li><li>Experience in regulated environments like Banking or Healthcare.</li><li>Understanding of security and compliance standards for AI systems.</li></ul><h3>Work Arrangements</h3><ul><li>Full-time position</li><li>Location: Bengaluru, Karnataka, India</li></ul>

Requirements

Benefits