Job description
Applied ML Engineer
Applied ML Engineer to build and productionize ML models for the NBA Decision Engine, using Python (TensorFlow/PyTorch/scikit-learn) for propensity/ranking/uplift/optimization and serving low-latency APIs. Integrate with feature stores, streaming (Kafka), and Node.js/Python decisioning services, owning MLOps (versioning, monitoring, retraining) plus explainability, bias, and guardrails for regulated environments.
Machine Learning: Advanced, Machine Learning Operations: Advanced
Applied ML Engineer to build and productionize ML models for the NBA Decision Engine, using Python (TensorFlow/PyTorch/scikit-learn) for propensity/ranking/uplift/optimization and serving low-latency APIs. Integrate with feature stores, streaming (Kafka), and Node.js/Python decisioning services, owning MLOps (versioning, monitoring, retraining) plus explainability, bias, and guardrails for regulated environments.
Machine Learning: Advanced, Machine Learning Operations: Advanced
Range of Year Experience-Min Year
5
Physical Location
Bangalore
Qualifications
BE
Range of Year Experience-Max Year
9