ML Ops

Prior ~2+ years of experience working with ML Ops & DSResponsibilities & Skills :Deploy, monitor, and scale ML models on AWS (SageMaker, EKS, Lambda) or GCP (Vertex AI, GKE, Cloud Functions) .Build and maintain CI/CD pipelines for ML workflows using GitHub Actions / Jenkins / cloud-native tools .Containerize and orchestrate workloads with Docker & Kubernetes ; manage infra via Terraform/CloudFormation .Implement model registries, feature stores, and observability using MLflow, Feast, Prometheus/Grafana .Collaborate with data scientists to operationalize ML models for personalization, recommendations, NLP .Proficient in Python , ML frameworks ( Scikit-learn, TensorFlow, PyTorch ) and data pipelines ( Airflow, Spark, SQL ).Bonus: experience with real-time ML serving, A/B testing, or media/recommender systems .Nice-to-Have:Experience with subscription, media, or recommender systems .Knowledge of experiment design & causal inference .Exposure to real-time ML serving (KFServing, Seldon, Ray Serve).Education:Btech /Mtech