Senior MLOps Engineer

3 days ago

New Delhi, India Atomic North Full time

Hiring: MLOps Engineer Experience:5–8 Years (with at least 2+ years in MLOps or ML deployment roles) Location:Bengaluru, Bhopal, Gurgaon, Hyderabad, Jaipur, Mumbai, Pune , ChennaiAbout the Role We are seeking askilled MLOps Engineerto operationalize and scale machine learning solutions on AWS. The ideal candidate will have strong expertise in cloud infrastructure, automation, and ML lifecycle management — from model training to deployment and monitoring — ensuring efficient and secure ML operations.Key Responsibilities Design and implementend-to-end MLOps pipelinesusing AWS SageMaker, Lambda, and Step Functions. Automate model deployment, monitoring, and retraining workflows for high availability and performance. Collaborate with data scientists to streamline model experimentation, versioning, and governance. Manage infrastructure-as-code usingTerraformorCloudFormationfor scalable and repeatable environments. ImplementCI/CD pipelinesfor ML models and data workflows using Jenkins, GitLab, or similar tools. Set up and maintainmonitoring, logging, and alertingsystems with AWS CloudWatch and native services. Enforce model governance, approval workflows, and compliance practices. Partner with DevOps and Data Engineering teams to standardize MLOps best practices. Continuously optimize ML model performance, reliability, and cost efficiency.Skills & Requirements 5–8 yearsof experience, with2+ years in MLOps or ML deploymentroles. Strong knowledge ofAWS services: SageMaker, Lambda, S3, Glue, CloudWatch. Proficient inPythonand infrastructure automation usingTerraformorCloudFormation. Experience withCI/CD tools,model monitoring, and orchestration (AWS Step Functions, Airflow). Understanding ofdata governance,model approval workflows, andaudit practices.Good to Have AWS Certifications(Machine Learning – Specialty, Solutions Architect). Exposure toAWS Redshift,Athena, orFeature Stores. Familiarity withDocker,Kubernetes, orEKSfor containerized ML deployments. Experience withMLfloworSageMaker Model Registryfor model management. Understanding offeature engineering pipelinesanddata versioningtools (DVC, Git LFS).Education Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

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