ML Ops

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