ML Ops

Prior~2+ yearsof experience working with ML Ops & DSResponsibilities & Skills : Deploy, monitor, and scale ML models onAWS (SageMaker, EKS, Lambda)orGCP (Vertex AI, GKE, Cloud Functions) . Build and maintainCI/CD pipelinesfor ML workflows usingGitHub Actions / Jenkins / cloud-native tools . Containerize and orchestrate workloads withDocker & Kubernetes ; manage infra viaTerraform/CloudFormation . Implementmodel registries, feature stores, and observabilityusingMLflow, Feast, Prometheus/Grafana . Collaborate with data scientists to operationalize ML models forpersonalization, recommendations, NLP . Proficient inPython , ML frameworks ( Scikit-learn, TensorFlow, PyTorch ) and data pipelines ( Airflow, Spark, SQL ). Bonus: experience withreal-time ML serving, A/B testing, or media/recommender systems .Nice-to-Have: Experience withsubscription, media, or recommender systems . Knowledge ofexperiment design & causal inference . Exposure toreal-time ML serving(KFServing, Seldon, Ray Serve).Education: Btech /Mtech

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