AML- Jr. AI / ML Modelling Engineer

About the Role

Join BNP Paribas as a Jr. AI/ML Modelling Engineer within our Anti-Money Laundering (AML) IT function in Mumbai. This role sits at the heart of Corporate & Institutional Banking technology, transforming raw transaction data into actionable intelligence to protect against fraud and financial crime.

Your Mission

You will design, train, and deploy next-generation machine learning models using advanced techniques like Neural Networks (NNs), Graph Neural Networks (GNNs), gradient-boosted ensembles, and unsupervised anomaly detection. Your work is vital for shaping the core detection capability of our platform across global operations.

Key Responsibilities

• Model Development & Evaluation: Build robust models detecting money laundering at transaction, client, and network levels using frameworks like PyTorch, XGBoost, and TensorFlow. Handle class imbalance and ensure statistical rigor.
• Data Engineering Pipeline: Construct optimized Spark/Delta Lake pipelines for feature consistency between training environments and production systems.
• MLOps & Lifecycle Management: Utilize MLflow for experiment tracking, model versioning, and champion-challenger workflows. Implement CI/CD pipelines using GitOps/Argo CD for seamless A/B testing.
• Deployment & Inference: Deploy low-latency inference services on Kubernetes platforms (using BentoML) with secure code practices including OAuth2/JWT and GDPR compliance.
• Governance & Explainability: Provide clear model explanations for audits, ensuring full reproducibility and alignment with regulatory obligations. Map scores to probabilities for reliable risk decision-making.

Technical Expertise Required

We seek engineers proficient in Python (OOP, modular design), SQL/NoSQL databases (Cassandra, Neo4j, PostgreSQL), cloud platforms (AWS/Azure/GCP), and containerization technologies. Knowledge of Kafka/RabbitMQ for streaming data is essential.

Career Growth

While direct AML experience isn't mandatory, a strong engineering foundation and willingness to learn financial crime domains are crucial. You will operate in a globally distributed environment, collaborating with data engineers, graph specialists, and compliance analysts. This role offers mentorship opportunities and end-to-end ownership of production-grade solutions.