AI/ML Engineering Manager

About The Role

We are looking for an experienced Lead AI/ML Engineering Manager to lead AI Product Pods across Credit Risk, Fraud Risk Management (FRM), and Collections & Recovery. The ideal candidate will have extensive experience building and deploying production-grade Machine Learning systems that deliver measurable business impact across the lending lifecycle.

This role requires strong technical leadership, hands-on AI/ML expertise, and experience leading high-performing engineering teams within regulated BFSI environments.

Key Responsibilities

Lead AI Product Pods across Credit Risk, Fraud Risk Management, and Collections functions.

Design, develop, and deploy production-scale Machine Learning systems for lending lifecycle decisioning.

Own the complete ML lifecycle including

Feature Engineering

Model Training

Model Evaluation

Deployment

Monitoring

Continuous Improvement

Design scalable ML platforms including

Distributed ML Infrastructure

Feature Stores

Model Registry

MLOps Pipelines

Develop AI solutions for

Credit Underwriting

Credit Risk Models

Fraud Detection

Graph ML

Early Warning Systems

Portfolio Risk Monitoring

Collections Optimisation

Recovery Forecasting

Propensity Models

Drive model governance, explainability, monitoring, compliance, and audit readiness in accordance with BFSI regulations.

Collaborate with Product, Engineering, Risk, Data Science, and Business stakeholders to deliver AI-driven outcomes.

Define AI platform architecture, operational excellence, SLAs, production monitoring, and incident management practices.

Build, mentor, and scale high-performing AI Engineering and Data Science teams.

Mandatory Requirements Experience

10 years of experience in AI Engineering, Data Science, or Machine Learning.

Current designation must be Lead or above (Lead / Principal / Engineering Manager / Associate Director / Director).

Strong experience building production-grade Machine Learning systems.

Hands-on experience developing AI/ML solutions in

Credit Risk

Fraud Risk Management (FRM)

Collections & Recovery

Proven experience designing and deploying large-scale distributed ML systems, including:

Model Training

Fine-tuning

Inference

Scalable Model Serving

Production Deployment

Strong leadership experience managing AI/ML teams and delivering end-to-end enterprise AI platforms.

Technical Skills Programming

Python (Expert)

AI/ML

Machine Learning

Deep Learning

Feature Engineering

Model Explainability

Model Monitoring

MLOps

Distributed Machine Learning

Big Data & Infrastructure

Apache Spark

Apache Kafka

Kubernetes

Distributed Computing

REST APIs / Microservices

CI/CD Pipelines

Feature Store

Model Registry

AI Solutions Experience

Must have experience building one or more of the following

Credit Risk Models

Fraud Detection Models

Graph Machine Learning

Early Warning Systems

Portfolio Monitoring

Collections Optimisation

Recovery Forecasting

Propensity Models

BFSI Governance

Hands-on Experience With

PII Handling

Model Governance

Model Risk Management

Auditability

Compliance

Secure-by-Design Architecture

Approval Workflows

Educational Qualification

Mandatory

B.Tech / M.Tech from Tier-1 institutes

IITs

NITs

BITS Pilani< .