Senior Machine Learning Engineer

Capgemini; Brussel; On-site; EUR 60,000 - 90,000; Full time

Job summary

Capgemini is seeking ML Engineers to work with Data Scientists to translate business requirements into production-ready ML solutions, selecting run infrastructure and serving models to meet real-time and volumetric needs.

You will automate ML pipelines, build container images, and support CI/CD workflows to deploy and monitor AI services in production environments.

Qualifications

• At least 4 years of relevant experience.
• Experience with package management and dependency handling.
• Knowledge of agile methodologies and collaboration across teams.

Responsibilities

• Working with Data Scientists to define and develop production-ready ML solutions with constraints in mind.
• Contribute to automation of ML pipeline elements to enable production deployment and testing.
• Support Data Scientists in using industrial solutions and CI/CD tools for AI services.
• Assist IT Production with parameterization of target environments and monitoring of models in production.

Skills

Package management

Agile methodology

System integration

Data visualization

Tools

Docker

CI/CD tools

Job description

ML Engineers contribute to Machine Learning projects by:

• Working with the Data Scientists to define and develop the target solution with production constraints in mind. This allows to select the correct run infrastructure and serving model (e.g. data ingestion scheme, API synchronicity, …) to address the business requirements (real-time responses, processing volumetry, …)
• Contributing to the automation of the different elements of the ML pipeline in order to integrate and deploy them in the production environment (e.g. building Docker/VM images, prepare unitary, regression and integration tests, …)
• Supporting Data Scientists on the usage of the existing industrial solutions available to build and monitor AI services (i.e. the CI/CD tools)
• Supporting IT Production on the parameterization of the target environment Ensuring that the model runs without errors, is retrained if needed (incl. automatically) and is monitored both from the IT and the business perspective.

Required experience / Knowledge:

At least 4 years of relevant experience

Technical experience:

Mandatory:

• Usage of package management tools and experience in dependency management
• Knowledge of agile methodology
• Experience with integration using different technologies (distributes/mainframe) and infra components
• Data visualization tools Business experience:

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