Ai/ml Engineer

BNP Paribas Group

BNP Paribas is one of the euro zone’s leading banks, with nearly 200 000 employees in 74 countries with key positions in its three main activities: Retail Banking, Investment & Protection Services, International Financial Services and Corporate & Institutional Banking.

Throughout the world, BNP Paribas employees are deeply involved with the real economy. They help women and men, as well as businesses, associations, and institutions, to build their projects and solve concrete problems. As an international company and one of the largest banks, we have the human, technological and financial means to help move the lines, to be part of the solution, to be forerunners. Our company is renewing its client-centered model to become more digital. This move goes hand in hand with our focus on bringing positive contributions to society.

AIR Tech team

Our AIR Tech team (Artificial Intelligence & Robotics Technology for RISK and Compliance) is here to drive the bank's digital transformation through the development of strategies and recommendations based on advanced analytical methods.

Within the RISK and Compliance functions, AIR Tech is an AI (Artificial Intelligence) expert team in charge of developing Artificial Intelligence solutions for RISK and Compliance Streams and beyond.

Role responsibilities

As an AI/ML (Artificial Intelligence / Machine Learning) Engineer, you will play a pivotal role in deploying AI models that drive strategic decision-making and operational efficiency. The ML Engineer will collaborate with cross-functional teams to integrate machine learning and other AI models into the business processes and provide technical support to ensure the success of AI initiatives.

Within our team of c.35 people, you will work closely with Data Scientists and contribute to industrializing the analysis and modelling of structured and unstructured data. You will also contribute to the architecture design of the solution for your project. And you will participate in the team effort in building tools and frameworks to improve efficiency with a focus on delivering high standard code and models.

You will also be involved in the MLOps activities, especially in deploying and monitoring our ML models in production. You will work closely with Data Scientists to define and operate an AI model lifecycle and to ensure the optimal performance of our portfolio of models.

Key Responsibilities

Integration of machine learning models into business processes, ensuring smooth deployment and effective performance.

Full stack development (front-end/back-end) and architecture design for projects but also development of some API based on common data processing needs.

Technical buddying with Data Scientists in terms of ensuring proper code structuring and better automation of workflows.

Technology monitoring on artificial intelligence topic (for instance review of internal or external solutions.

Beyond projects, AI/ML Engineers are expected to share their expertise at multiple levels: within the team though technical sharing sessions and beyond as well during our regular open discussion sessions on AI.

Technical Skills and Qualifications

Expertise: Python (mandatory), Structured (SQL) and No-SQL (ElasticSearch) Databases, Containerization (Docker, Kubernetes), DevOps and MLOps methodologies, Web frameworks (Angular, JavaScript, Flask, React, Apache).
- Education: Bachelor or Master’s Degree in Computer Science or related field.
- Experience: at least 2-year experience as software engineer/ data analytics engineer in an agile, innovation-oriented team, preferably with at least one of the following skills:
In particular experience building and maintaining CI/CD pipelines using tools such as Ansible, Jenkins, Docker, and Kubernetes, or building, deploying, and monitoring ML models in production using tools such as MLFlow and Kubeflow.
- Languages:Fluent in English. Spanish and/or French a plus.
- Personal profile:
- Strong analytical / problem solving skills.
- Capacity to work in project mode.
- Team player.
- Rigorous and curious.
- Resourceful.
- Client-oriented.

**DIVERSITY AND INCLUSION COMMITMENT**: