Machine Learning Engineer

POSITION OVERVIEW The Machine Learning Engineer will be a core member of the Tribe AI (ISPL ITG Fortis ADM) at BNP Paribas Fortis. Based in Chennai and working in the Brussels time‑zone, you will turn data‑science prototypes into production‑ready, secure and scalable AI services. The role combines strategic design with day‑to‑day operational ownership of ML pipelines, Python environments, and MLOps tooling.

JOB RESPONSIBILITIES Design, build and optimise data‑sourcing pipelines (ETL, CFT, Denodo, Airflow) to feed AI/ML use cases. Integrate new internal or external data sources (APIs, databases, streaming platforms) while respecting data‑governance, latency and quality constraints. Audit, upgrade and maintain Python dependencies (pip, uv, mamba/micromamba) across development, testing and production.

Run regular security scans, patch critical vulnerabilities and enforce secure‑coding practices. Automate compliance checks in CI/CD pipelines to block vulnerable code from reaching production. Own CI/CD workflows (Jenkins, GitLab CI/CD) for containerised ML models (Docker, Kubernetes), ensuring versioning, roll‑backs and smooth deployments.

Work with Data Scientists and Production IT to define production‑ready architectures that meet real‑time and high‑volume processing needs. Troubleshoot and resolve complex incidents in QA or Production, driving continuous improvement of AI services. Implement advanced logging, monitoring and alerting (e.g., Grafana, Kibana) and lead post‑mortem analyses.

Promote software‑engineering best practices – code quality, testing, documentation and security – within the squad. Stay up‑to‑date with AI/ML trends (LLMs, agentic AI) and propose innovative solutions that accelerate time‑to‑market. REQUIRED EDUCATION, SKILLS, AND EXPERIENCE (MUST‑HAVE) Master’s degree (or equivalent) in Computer Science, Engineering, Data Science or a related discipline.

Minimum 6 years of relevant experience, including at least 4 years of professional Python development (object‑oriented programming, decorators, performance optimisation, security). Strong Python environment management (uv, pip, mamba/micromamba). Proven MLOps experience: model versioning, deployment, CI/CD, artifact handling.

Containerisation and orchestration with Docker and Kubernetes (scaling, resource management). Advanced CI/CD pipelines using Jenkins and/or GitLab CI/CD. Linux system administration and Bash scripting.

PostgreSQL expertise – query optimisation, schema design. Deep knowledge of the Denodo Platform: configuring virtual data layers, writing efficient VQL, creating logical views and API integrations. Airflow proficiency: designing robust DAGs, creating custom operators/hooks, integrating with Denodo, PostgreSQL, S3, MLflow/Kubeflow, and tuning performance (parallelism, executor selection, XCom handling).

Monitoring and incident‑management skills: structured logging, debugging complex failures, building dashboards. PREFERRED EDUCATION, SKILLS, AND EXPERIENCE (NICE‑TO‑HAVE) API design and development experience (e.g., Django REST Framework). Experience with distributed processing frameworks such as Spark or Hadoop.

Knowledge of model‑compression techniques (quantisation, pruning, etc.). Familiarity with data‑visualisation and observability tools (Kafka, ELK stack, Grafana, Kibana) for real‑time monitoring dashboards. Hands‑on experience with cloud platforms (AWS, Azure, GCP) and infrastructure‑as‑code tools (Terraform, Ansible).

About BNP Paribas India Solutions BNP Paribas India Solutions, a wholly‑owned subsidiary of BNP Paribas SA, operates 24 × 7 delivery centers in Bengaluru, Chennai and Mumbai. With more than 10 000 professionals, we support the Group’s Corporate & Institutional Banking, Investment Solutions and Retail Banking businesses worldwide. BNP Paribas is an equal‑opportunity employer.

We celebrate diversity and are committed to creating an inclusive environment for all employees.