Job Title

Prior ~2+ years of experience working with ML Ops & DS Responsibilities & 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