Manager (M1)- ML Engineers

• Strong proficiency in Python and SQL , with hands-on experience in Scikit-learn, XGBoost/LightGBM and TensorFlow/PyTorch.
• Strong experience building predictive and decisioning models using behavioural, transactional, bureau and other customer data.
• Experience with models/use cases such as Next Best Action, propensity modelling, payment/bounce prediction, customer segmentation, risk or response prediction .
• Hands-on experience taking ML models to production, including validation, monitoring, performance analysis and retraining .
• Strong statistical and modelling discipline, with the ability to identify data leakage, instability, bias and genuine predictive lift .
• Ability to translate ambiguous business problems into end-to-end ML/AI solutions and communicate trade-offs clearly to product, business and engineering teams.
• Working understanding of LLMs and Agentic AI , with the ability to integrate predictive ML models into larger AI/agentic decisioning workflows.

• Experience with Next Best Action / recommendation / optimization / propensity modelling .
• Exposure to LLMs, agentic workflows, RAG or AI-driven decision systems .
• Working knowledge of AWS/GCP for ML and data workloads.
• Experience with MLOps - Git/DVC, experiment tracking, CI/CD, model monitoring and automated retraining.
• Sound understanding of data architecture, feature pipelines and low-latency model serving .

Required Skills