Machine Learning Engineer Consultant

• Work with Data Scientists to define and develop target solutions with production constraints in mind, selecting the correct infrastructure and serving model to address business requirements such as real-time responses and processing volumetry.
• Contribute to the automation of ML pipeline elements to integrate and deploy them in production environments, including building Docker/VM images and preparing unit, regression, and integration tests.
• Support Data Scientists in using existing industrial solutions for building and monitoring AI services, including CI/CD tools.
• Support IT Production in parameterizing the target environment.
• Ensure models run without errors, are retrained as needed (including automatically), and are monitored from both IT and business perspectives., * Consultancy Nature: Embrace your identity as a consultant, working on-site and representing Keystone Solutions in every engagement.
• Dynamic Projects: Experience a wide variety of challenges across different client environments, ensuring no two missions are ever the same.
• Turbo-Charged Learning: Accelerate your professional development and broaden your expertise through exposure to diverse technologies and business contexts.
• Skyrocketing Ambition: Grow your career within a framework that values ambition and supports your upward trajectory.
• K-Stone Values: As a K-Stone, you bring our core values to every project, making a real impact for clients and colleagues alike.

If you are ready to tackle technical and strategic challenges in a dynamic consultancy environment, apply today .

Do you have experience in Virtualization?, * Dutch: is a plus

• French: is a plus
• English: is mandatory, * At least 4 years of relevant experience

Technical Experience (Mandatory):

• Containerization / virtualization
• AI platforms & IDEs
• CI/CD (gitlab-ci)
• Code, model & data versioning
• Python advanced
• Usage of package management tools and experience in dependency management
• PostgreSQL

Technical Experience (Preferable):

• Experience with integration using different technologies (distributed/mainframe) and infrastructure components
• Model compression techniques
• ELT / ETL tools
• Big data tools (Spark)
• Data flow processing
• Data visualization tools

Business Experience (Mandatory):

• Knowledge of agile methodology

Soft Skills:

• Communication skills - oral & written
• Ability to deliver/results driven
• Attention to detail/rigor
• Creativity & innovation/problem solving
• Proactively invests time in continuous learning and knowledge improvement
• Demonstrates awareness of efficiency and efficacy
• Thinks out of the box outside existing processes and frameworks
• Works with energy and empowerment to deliver great results and contribute to company success
• Is constructive by being open to changes and others' opinions, ideas, and feedback