Notre client dans le secteur Banque et finance recherche un Machine Learning Engineer H/F Descriptif de la mission:

Job description – Machine Learning Engineer

Mission context

Machine Learning Engineers promote the adoption of best standards in industrial code development across the ML & AI community. They develop machine learning pipelines that are production-ready by design or integrate existing machine learning solutions into industrial pipelines.

They participate in the development, deployment and monitoring of AI services. This includes contributing to data quality checks, data flow design, model design and overall integration into the production environment. They also facilitate communication between AI & Analytics teams and IT Production regarding ML model deployment, ensuring that models moved to production are supported by the appropriate data pipelines and monitoring.

Main responsibilities

The Machine Learning Engineer contributes to machine learning projects by:

• Working with Data Scientists to define and develop the target solution while taking production constraints into account

• Helping select the appropriate runtime infrastructure and serving model based on business requirements such as real-time response needs, processing volumes, data ingestion schemes and API synchronicity

• Contributing to the automation of the different elements of the ML pipeline to enable integration and deployment into production

• Building Docker or virtual machine images and preparing unit, regression and integration tests

• Supporting Data Scientists in the use of existing industrial solutions used to build and monitor AI services, including CI/CD tools

• Supporting IT Production in the parameterization of the target environment

• Ensuring that models run without errors, are retrained when needed, including automatically, and are monitored from both IT and business perspectives

Profile required

Experience

• At least 4 years of relevant experience

Technical skills – mandatory

• Containerization / virtualisation

• AI platforms and IDEs

• CI/CD (GitLab CI)

• Code, model and data versioning

• Advanced Python

• Usage of package management tools and dependency management

• PostgreSQL

Technical skills – preferable

• Experience with integration using different technologies, including distributed and mainframe environments, and infrastructure components

• Model compression techniques

• ELT / ETL tools

• Big data tools such as Spark

• Data flow processing

• Data visualization tools

Business knowledge

• Knowledge of agile methodology

Language requirements

• English is mandatory

• Dutch is a plus

• French is a plus

Soft skills

• Strong oral and written communication skills

• Results-driven mindset and ability to deliver

• Attention to detail and rigor

• Creativity, innovation and problem-solving

• Continuous learning mindset and willingness to improve knowledge

• Awareness of efficiency and efficacy

• Ability to think outside existing processes and frameworks

• Energy, ownership and commitment to delivering strong results

• Openness to change and to others' opinions, ideas and feedback

Work organization

• Expected setup: 50% on site and 50% homeworking

Expected deliverables

• Production-ready ML pipelines

• Integrated and deployable ML solutions

• Automated pipeline components

• Monitored and maintainable AI services in production

Mandatory skills: Advanced Python,CI/CD (GitLab CI),Containerization / virtualisation,ML pipeline industrialization,PostgreSQL,English

Nice to have: Dutch or French, integration with distributed/mainframe technologies, model compression techniques, ELT / ETL tools, Spark, data flow processing, data visualization tools