Junior Infrastructure AI Specialist
The role
As a Junior Infrastructure AI Specialist, you will work at the intersection of platform engineering and applied AI. You will contribute to the integration of artificial intelligence and machine learning capabilities into infrastructure platforms and IT operations. You will help build MLOps pipelines, deploy AI/ML models on cloud infrastructure, and apply generative AI to improve infrastructure automation, observability, and service reliability. This forward-looking role positions you on one of the most strategic disciplines in today's technology market, within a practice that is shaping how enterprise infrastructure is operated in the AI era.
Key responsibilities
- Contribute to building and maintaining MLOps pipelines for model training, evaluation, and deployment.
- Support the deployment of AI/ML models on cloud platforms (AWS SageMaker, Azure ML, Vertex AI).
- Help implement CI/CD workflows for AI model lifecycle management (MLflow, Kubeflow, Azure ML Pipelines).
- Contribute to the development of RAG-based and GenAI-powered infrastructure automation use cases.
- Develop and maintain data pipelines feeding AI/ML workloads from infrastructure telemetry.
- Monitor AI model performance in production and support retraining workflows when drift is detected.
- Collaborate with infrastructure teams to provision GPU/TPU compute resources for AI workloads.
- Document AI solutions: model cards, operational runbooks, and exploitation guides.
- Contribute to testing procedures and automated validation of AI/ML models in production.
- Stay current with evolving AI tools, GenAI frameworks, and AI trends applied to infrastructure.
- Participate in troubleshooting, root cause analysis, and continuous improvement of AI-driven services in production environments.
- Assist in integrating AI solutions with enterprise platforms, APIs, ITSM tools, monitoring systems, and automation workflows.
Who We Are
Your Profile
Language Requirements
- Fluency in English and French and/or Dutch is required.
- Ability to work effectively in an international and multicultural environment.
Required Skills
- Proficiency in Python for data processing, model development, and automation scripting.
- Foundational understanding of machine learning concepts and frameworks (TensorFlow, PyTorch, scikit-learn).
- Working knowledge of cloud AI/ML services (AWS SageMaker, Azure ML, or Vertex AI).
- Understanding of REST APIs, JSON, and system integration principles to connect AI agents with enterprise applications and operational tools.
- Experience using Git, GitHub/GitLab, and collaborative software development practices.
- Knowledge of data quality, data lineage, and data governance concepts supporting AI and ML workloads.
- Understanding of containerisation (Docker) and basic Kubernetes for ML workload deployment.
- Familiarity with MLOps tools: MLflow, Weights & Biases, or equivalent experiment tracking platforms.
- Basic knowledge of vector databases (Pinecone, Weaviate, pgvector) and RAG architectures.
- Analytical, problem-solving mindset with strong attention to detail.
- Fluency in French (mandatory) and professional-level English (mandatory).
Preferred Skills
- Experience with LLM fine-tuning or prompt engineering for infrastructure automation tasks.
- Familiarity with AIOps tools (Dynatrace, New Relic AI, or Datadog AI).
- Exposure to agentic AI frameworks (LangChain, AutoGen, CrewAI, LlamaIndex).
- Awareness of data privacy, AI ethics, and bias mitigation principles.
- Basic knowledge of distributed computing and GPU resource management.
- Familiarity with scripting and automation technologies such as PowerShell, Bash, or Python automation frameworks.
- Exposure to enterprise search technologies, knowledge management platforms, and document processing solutions.
- Familiarity with prompt lifecycle management, prompt testing, and prompt optimization techniques.
Relevant Certifications
- AWS Certified Machine Learning – Specialty.
- Microsoft Certified: Azure AI Engineer Associate (AI-102).
- Google Professional Machine Learning Engineer.
- TensorFlow Developer Certificate.
- DeepLearning.AI MLOps Specialization.
- Databricks Generative AI Fundamentals or equivalent GenAI certification.
- Generative AI certification covering prompt engineering, RAG, AI agents, and responsible AI practices.
Additional Requirements
- Candidates must be citizens of a NATO member country.
- Candidates must be eligible to work in Belgium.
Our offer
- 13th month + holiday allowance: Ensuring financial stability and recognition for your hard work.
- 20 + 12 holidays: Providing ample time to recharge and spend quality moments with loved ones.
- Laptop and smartphone: Equipping you with the necessary tools to excel in your role, regardless of location.
- Hospitalization insurance and extensive group insurance package: Prioritizing your health and well-being, so you can focus on what matters most.
- Extensive level of flexibility: Allowing you to decide
- Bonus program: Recognizing and rewarding your exceptional contributions to the team's success.
- Training & learning opportunities: Encouraging continuous growth and skill development to reach your full potential.
- Green mobility program: Supporting environmentally friendly commuting options like e-bikes, public transport, bike 2 work allowance, and more.
- Flexrewards: Empowering you to customize your rewards package with our flexible benefits tool to suit your individual needs.
- Discount program: Offering discounts at your favorite online shops, so you can enjoy life outside of work.
- Employee shares purchase plan: Providing an opportunity to become a stakeholder in the company's success.
- Eco-cheques: Promoting sustainable living and environmentally conscious choices.
- And many more!
Brussels
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