Role & responsibilities
Clean, analyse and prepare datasets; build ML feature and training pipelines.
Develop, test and optimise ML models for fraud detection and risk scoring.
Evaluate model performance using precision, recall and false-positive metrics.
Monitor model performance, data drift and retrain models as required.
Collaborate with backend and SDK engineers to deploy and integrate ML models.

Preferred candidate profile
Hands-on experience with Python, NumPy, pandas and PyTorch or TensorFlow.
Solid understanding of Machine Learning, neural networks and sequence modelling.
Knowledge of SQL, EDA, data pipelines and imbalanced datasets.
Experience in model evaluation, experimentation and version control.
Proficiency in AI coding tools and ability to review and test generated code.

Positive to Have: SHAP, graph features, experiment tracking, computer vision, liveness detection or deepfake evaluation.

📌 Ai Ml Engineer Delhi
🏢 Talent Corner HR Services
📍 Delhi