Job Specifications
Budget: 650-750
Context
As part of an Employee Virtual Assistant initiative, the mission is to help turn a product vision into a coherent technical implementation roadmap. The role focuses on structuring and deploying Python micro-services, ensuring clear service boundaries so multiple teams can work efficiently in parallel. You will also promote industrial engineering standards across the ML&AI community by enabling production-ready ML pipelines and the integration, deployment, and monitoring of AI services in close collaboration with Data Scientists and IT Production.
Responsibilities
Structure the technical vision into a clear implementation roadmap for the employee virtual assistant
Design and define micro-service boundaries to enable parallel delivery across teams
Develop, deploy, and maintain Python micro-services for AI/ML services
Work with Data Scientists to define target solutions with production constraints (e.g., data ingestion, API synchronicity, volumetry, real-time needs)
Contribute to ML pipeline automation for production integration and deployment (e.g., Docker/VM images, unit, regression and integration tests)
Support Data Scientists in using existing industrial solutions for building and monitoring AI services (e.g., CI/CD tools)
Support IT Production in target environment parameterization
Contribute to monitoring, retraining (including automation where applicable), and ensuring models run reliably without errors
Share knowledge and best practices within the chapter (Swagger, mocking, testing)
Technical Skills
Must have
At least 6 years of relevant experience
Proven experience building and deploying Python micro-services
Strong knowledge of:
Containerization
CI/CD
Code, model & data versioning
Cloud computing services
Relational databases
Swagger / schema definition
AI platforms & IDEs
Experience contributing to development, deployment, and monitoring of AI services (data quality checks, data flow design, model integration)
Project coordination experience
Strong communication skills (oral & written)
Results-driven mindset with high attention to detail and rigor
Proactive continuous learning and knowledge sharing attitude
English: mandatory
Education: Master’s in Computer Science or related field/experience
Should have
Knowledge of mocking and testing practices (and willingness to coach others)
Certifications in Linux, Python, and/or Data Science (a plus)
Familiarity with ML packages and libraries relevant to the entity/project
Ability to facilitate communication between AI & Analytics teams and IT Production regarding ML deployment
Nice to have
Dutch (nice to have)
French (nice to have)
Knowledge of the IT language of the entity/project (preferred)
Experience with model compression techniques
Who We Are
Community Consulting goes beyond traditional consulting; it’s all about fostering connections in an atmosphere of trust and confidence.
Transparency & Honesty : We say things as they are. Clear communication for seamless collaboration.
#COMMUNITEAM : Work independently, but never alone. Collective intelligence drives us further, faster.
Total Commitment : Always present, always engaged. We find solutions and make sure everyone moves forward together.
Guaranteed Efficiency : No fluff, just results. We act fast, keep our promises, and deliver top quality.
This is our DNA. This is how we make a difference.
Type
Permanent or Freelance
Contract
Full-time
Location
Brussels
Homeworking
2 days per week
Sector
Bank
Keywords
Python microservices
ML pipelines
CI/CD & MLOps
You Career Advisor
Lena Vandecnocke
Lead Talent Management & Business Ops
l.vandecnocke@communityconsulting.be
https://www.communityconsulting.be/jobs/ml/
About the Company
Une plateforme, deux volets : 1) un volet recruteur, la MegaSearch, pour sourcer, contacter et recruter sans commission les 500,000 freelances de Collective (vive l'IA !). => Par ici pour avoir une démo de l'interface Recruteur : https://calendly.com/juliette-collective-work/demo-collective-work-clone 2) un volet freelance pour se rendre visible et joinable des recruteurs, développer son réseau, et se professionnaliser via des outils de gestion. Faites comme 2,500 ESN, entreprises, cabinets et agences (Theodo, Artefact, Cher...
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