BNP Paribas
Website:
bnpp.lk
Company:
https://www.linkedin.com/company/bnp-paribas
Seniority: Not Applicable
Industries: Banking
Job details:
About Business Line/Function
The AML IT function sits within the BNP Paribas Corporate & Institutional Banking (CIB) CEFS‑technology ecosystem and provides end‑to‑end technology platform that enables the bank’s anti‑money‑laundering (AML) program. Its core purpose is to translate regulatory and compliance requirements into robust, scalable, and secure IT solutions that detect, investigate, and report suspicious activity across the Group’s global operations.
The AML IT business line is the technology backbone that transforms raw transaction data into actionable AML intelligence, ensuring that BNP Paribas CIB meets its regulatory obligations while maintaining operational resilience and innovation.
Position Purpose
The role centers on creating next‑generation AML capabilities and will be instrumental in protecting the BNPP Group from fraud, money‑laundering, and other financial crimes by using advanced technologies and innovative solutions.
As an AI-ML Engineer, you will design, train and deploy machine learning models that detect money laundering and financial crime. This position is vital for shaping the core detection capability of the platform. This also involves execution of various AML initiatives, thereby strengthening the organization’s overall risk management.
While direct AML experience is not mandatory, a strong foundation in machine learning, sound engineering practices, and a willingness to learn the financial-crime domain are essential. Familiarity with regulated environments, model governance, or fraud and anomaly detection is an advantage, but we are primarily looking for engineers who can build robust, well-calibrated, production-grade models and reason carefully about their real-world impact. The role will operate within a globally distributed environment.
Direct Responsibilities
- Model Development & Evaluation – Design, train, and assess ML models (NNs, GNNs, gradient‑boosted ensembles, unsupervised anomaly detectors) for money‑laundering detection across transaction, client, and network levels.
- Feature Engineering Pipeline – Build and optimise Spark/Delta Lake pipelines, ensuring feature consistency between training and production.
- Lifecycle Management – Track experiments, version models, and run champion‑challenger workflows with MLflow.
- Low‑Latency Deployment – Deploy and maintain inference services (e.g., BentoML) on the on‑prem Kubernetes platform.
- Calibration & Scoring – Calibrate models and map scores to probabilities to deliver reliable, decision‑ready risk scores.
- Explainability & Governance – Provide model explainability for audits, document design/assumptions/validation, and guarantee full reproducibility and auditability for regulatory compliance.
- Cross‑Functional Collaboration – Partner with data engineers, graph/LLM specialists, and compliance analysts to translate detection requirements into production‑ready models.
Technical & Behavioral Competencies
- Python engineering & secure code – Expert in object‑oriented, modular, and reusable Python code; packaging, logging, metrics, and tracing (ELK, Prometheus, Grafana, OpenTelemetry); security primitives (OAuth2/JWT) and data‑privacy compliance (GDPR/CCPA).
- ML modeling & calibration – Hands‑on with PyTorch (custom architectures, focal loss, training loops, GPU optimization), XGBoost/LightGBM, scikit‑learn/Keras/TensorFlow; deep knowledge of model calibration (Platt scaling, score‑to‑probability, MC‑Dropout), evaluation (PR/AUC‑ROC, F‑beta, lift charts) and handling class imbalance along with the underlying statistical concepts (calibration theory, hypothesis testing).
- Large‑scale data processing – Proficient in Pandas, Dask, Polars (or equivalent) for transactional‑scale datasets; feature engineering, distributed pipelines, and performance‑aware data handling.
- MLOps & lifecycle management – MLflow (experiment tracking, model registry, stage promotion), BentoML (runners, adaptive batching, CPU/GPU pools), GitOps/Argo CD for A/B‑testing and champion‑challenger workflows; CI/CD pipelines with Git/Bitbucket.
- Python microservices & containerization – Designing and deploying APIs with FastAPI, Flask, or Django; async I/O, Celery task queues, Docker packaging, and Kubernetes orchestration for scalable inference services.
- Data storage & query optimization – Strong command of SQL (PostgreSQL, Oracle) and NoSQL/graph stores (Cassandra, MongoDB, Neo4j, JanusGraph); schema design, indexing, and performance tuning.
- Experience with AWS, Azure, or GCP; messaging/streaming (Kafka, RabbitMQ); cross‑team and multi‑geography collaboration, rapid technology adoption, mentorship, and end‑to‑end ownership of solutions.
- Strong collaboration and learning mindset, with the ability to work across teams and geographies, adapt to new technologies, mentor others, and take end-to-end ownership.
Nice To Have Skills
- Experience with W&B alongside MLflow.
- Evidently AI or similar drift/monitoring platforms
- DVC or LakeFS for dataset versioning
- TorchServe / Triton / KServe (alternative serving paths)
- Exposure to large scale data or streaming platforms such as Spark, Flink, or similar frameworks in high volume processing contexts.
Education Level
Bachelor Degree or equivalent
Experience Level
At least 7 years
Job Title
AIML_Engineer
Date
18/05/2026
Department
CEP IT
Location:
Mumbai
Business Line
Anti Money Laundering
Reports To
AML IT Manager
About BNP Paribas India Solutions
Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, European Union’s leading bank with an international reach. With delivery centers located in Bengaluru, Chennai, and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 10000 employees, to provide support and develop best-in-class solutions.
About BNP Paribas Group
BNP Paribas is the European Union’s leading bank and key player in international banking. It operates in 65 countries and has nearly 185,000 employees, including more than 145,000 in Europe. The Group has key positions in its three main fields of activity: Commercial, Personal Banking & Services for the Group’s commercial & personal banking and several specialized businesses including BNP Paribas Personal Finance and Arval; Investment & Protection Services for savings, investment, and protection solutions; and Corporate & Institutional Banking, focused on corporate and institutional clients. Based on its strong diversified and integrated model, the Group helps all its clients (individuals, community associations, entrepreneurs, SMEs, corporate and institutional clients) to realize their projects through solutions spanning financing, investment, savings and protection insurance. In Europe, BNP Paribas has four domestic markets: Belgium, France, Italy, and Luxembourg. The Group is rolling out its integrated commercial & personal banking model across several Mediterranean countries, Turkey, and Eastern Europe. As a key player in international banking, the Group has leading platforms and business lines in Europe, a strong presence in the Americas as well as a solid and fast-growing business in Asia-Pacific. BNP Paribas has implemented a Corporate Social Responsibility approach in all its activities, enabling it to contribute to the construction of a sustainable future, while ensuring the Group's performance and stability
Commitment to Diversity and Inclusion
At BNP Paribas, we passionately embrace diversity and are committed to fostering an inclusive workplace where all employees are valued, respected, and can bring their authentic selves to work. We prohibit Discrimination and Harassment of any kind, and our policies promote equal employment opportunity for all employees and applicants, irrespective of, but not limited to their gender, gender identity, sex, sexual orientation, ethnicity, race, color, national origin, age, religion, social status, mental or physical disabilities, veteran status etc. As a global Bank, we truly believe that inclusion and diversity of our teams is key to our success in serving our clients and the communities we operate in.
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