1 day ago
Brussels, BelgiumEntry Level
Responsibilities
- Contribute to building and maintaining MLOps pipelines for model training, evaluation, deployment, and retraining.
- Deploy and operate AI/ML models on AWS SageMaker, Azure ML, and Vertex AI.
- Implement CI/CD workflows for AI model lifecycle management using MLflow, Kubeflow, and Azure ML Pipelines.
- Develop RAG-based and generative-AI infrastructure automation use cases.
- Develop and maintain data pipelines using infrastructure telemetry to feed AI/ML workloads.
- Monitor production model performance and support retraining when drift is detected.
- Help provision GPU/TPU compute resources for AI workloads with infrastructure teams.
- Document AI solutions through model cards, operational runbooks, and exploitation guides.
- Contribute to automated testing and validation of AI/ML models in production.
- Troubleshoot AI-driven production services, perform root cause analysis, and support continuous improvement.
- Integrate AI solutions with enterprise platforms, APIs, ITSM tools, monitoring systems, and automation workflows.
Requirements
- Proficiency in Python for data processing, model development, and automation scripting.
- Foundational understanding of machine learning concepts and TensorFlow, PyTorch, and scikit-learn.
- Working knowledge of AWS SageMaker, Azure ML, or Vertex AI.
- Understanding of REST APIs, JSON, and system integration principles.
- Experience using Git and GitHub/GitLab with collaborative software development practices.
- Knowledge of data quality, data lineage, and data governance for AI/ML workloads.
- Understanding of Docker and basic Kubernetes for ML workload deployment.
- Familiarity with MLflow, Weights & Biases, or equivalent experiment-tracking platforms.
- Basic knowledge of Pinecone, Weaviate, or pgvector and RAG architectures.
- Fluency in French and professional-level English, with the ability to work in international and multicultural environments.
- Candidates must be citizens of a NATO member country and eligible to work in Belgium.
- Preferred qualifications include LLM fine-tuning or prompt engineering, AIOps tools, agentic-AI frameworks, data privacy and AI ethics, distributed computing, GPU resource management, scripting and automation technologies, enterprise search, knowledge management, document processing, and prompt lifecycle management.
- Relevant preferred certifications include 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 generative-AI certification.
Benefits
- 13th-month payment and holiday allowance.
- 20 regular holidays plus 12 additional holidays.
- Laptop and smartphone.
- Hospitalization insurance and an extensive group insurance package.
- Extensive work flexibility.
- Bonus program.
- Training and learning opportunities.
- Green mobility program including e-bikes, public transport, and bike-to-work allowance.
- Flexrewards flexible benefits tool.
- Employee discount program.
- Employee share purchase plan.
- Eco-cheques.
Tech Stack
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.