Ai Ml Engineer
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Summary
AI/ML Engineer in New Delhi building and optimizing fraud-detection and risk-scoring models: preparing datasets, building feature/training pipelines, evaluating model performance, monitoring drift and retraining, and integrating models with backend/SDK teams. Core stack: Python, NumPy, pandas, PyTorch or TensorFlow, SQL.
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.
- Strong 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.
Good to Have: SHAP, graph features, experiment tracking, computer vision, liveness detection or deepfake evaluation.