
ML Ops
10 hours ago
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
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