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