Senior MLOps Engineer

About the Role

<h2>Senior MLOps Engineer</h2><p>We are seeking a Senior MLOps Engineer with 8?12 years of experience in designing enterprise-scale ML infrastructure and operational frameworks. The ideal candidate will have deep expertise in CI/CD automation, cloud-native ML deployment, observability, governance, and scalable AI platform engineering. You will lead MLOps initiatives, establish best practices, and drive automation strategies for secure and compliant AI model lifecycle management.</p><h3>Key Responsibilities</h3><ul><li>Architect and implement enterprise-grade MLOps platforms and deployment frameworks.</li><li>Lead automation of end-to-end ML lifecycle management.</li><li>Define CI/CD and governance standards for AI/ML systems.</li><li>Design scalable infrastructure for model serving and inference.</li><li>Implement advanced monitoring frameworks for model health, drift, latency, and reliability.</li><li>Collaborate with Data Science, Security, and Platform Engineering teams.</li><li>Optimize cloud infrastructure and ML workloads for scalability and performance.</li><li>Mentor junior engineers and establish operational best practices.</li><li>Ensure compliance, auditability, and security of AI deployments.</li><li>Drive adoption of modern MLOps and LLMOps practices.</li></ul><h3>Requirements</h3><ul><li>Strong expertise in Python, Kubernetes, Docker, Terraform, Linux.</li><li>Advanced experience with CI/CD pipelines, Jenkins, GitHub Actions, GitLab CI/CD.</li><li>Experience with MLflow, Kubeflow, Airflow, Model Registry.</li><li>Strong cloud expertise in AWS, Azure, GCP.</li><li>Experience in Model Deployment, Model Monitoring, Drift Detection, Infrastructure Automation.</li><li>Knowledge of Security and compliance frameworks, DevSecOps, Infrastructure as Code.</li><li>Strong leadership and stakeholder management skills.</li><li>Preferred experience with LLMOps, Generative AI deployment, Vector Databases, Feature Stores.</li><li>Expertise in SageMaker, Vertex AI, Azure ML.</li><li>Familiarity with Spark/PySpark, Kafka, Real-time ML systems.</li><li>Exposure to GPU infrastructure management, Distributed model serving.</li><li>Knowledge of Responsible AI and governance frameworks.</li><li>Experience in BFSI, Healthcare, or highly regulated industries.</li></ul><h3>Work Arrangements</h3><ul><li>Full-time position located in Bengaluru, Karnataka, India.</li><li>Remote work details not specified.</li></ul>

Requirements

Benefits