AI Engineer

Common Sense AI; Vlaanderen; Sur place; EUR 65 000 - 90 000; Plein temps

Résumé du poste

Common Sense AI seeks an AI Engineer to operate at the intersection of data science, ML, and Generative AI. You'll take ideas to production, building applied AI that delivers business impact.

You'll collaborate with data, engineering, and business stakeholders, applying ML models, LLMs, and GenAI pipelines across the full lifecycle, from data prep to monitoring. This role offers ownership and opportunities to grow into technical leadership.

Qualifications

• Strong foundation in data science and machine learning.
• Hands-on Python with ML libraries (scikit-learn, PyTorch, TensorFlow).
• Interest in Generative AI / LLMs (RAG, embeddings, prompt engineering).
• Solid software engineering mindset (clean code, version control, testing).
• Familiarity with cloud platforms (Azure, AWS, or GCP) and deployment patterns.
• Experience across the full AI lifecycle from data to production.
• Curious, pragmatic, and impact-driven mindset.

Responsabilités

• Design, build, and evaluate ML models (classification, regression, forecasting, NLP).
• Develop Generative AI solutions (LLMs, RAG pipelines, prompts, agents).
• Translate business problems into AI use cases with measurable impact.
• Prepare, explore, and model data with strong data science foundations.
• Build production-ready AI systems (APIs, pipelines, monitoring, retraining).
• Work with cloud and MLOps tooling to deploy and maintain models.
• Communicate clearly with technical and non-technical stakeholders.
• Stay up to date with evolving AI and GenAI best practices.

Connaissances

Data science & ML

Python

Generative AI / LLMs

Cloud platforms (Azure/AWS/GCP)

ML pipelines

Production systems

Stakeholder communication

Outils

LangChain

LlamaIndex

MLflow

CI/CD

Description du poste

About the role

We’re looking for an AI Engineer who sits comfortably at the intersection of data science, machine learning, and Generative AI.

You’ll work on real-world AI solutions, from classical ML models to LLM-powered applications, and take them all the way from idea to production. This is not a research-only role, and not a pure software role either: it’s about applied AI that delivers business impact.

You’ll collaborate closely with data, engineering, and business stakeholders, and help shape how AI is used responsibly and effectively.

What you’ll do

• Design, build, and evaluate machine learning models (classification, regression, forecasting, NLP, etc.)
• Develop Generative AI solutions (LLMs, RAG pipelines, prompt engineering, agents)
• Translate business problems into AI use cases with measurable impact
• Prepare, explore, and model data using strong data science foundations
• Build production-ready AI systems (APIs, pipelines, monitoring, retraining)
• Work with cloud and MLOps tooling to deploy and maintain models
• Communicate clearly with both technical and non-technical stakeholders
• Stay up to date with evolving AI and GenAI best practices

What you bring

• Strong foundation in data science & machine learning
• Hands-on experience with Python and ML libraries (e.g. scikit-learn, PyTorch, TensorFlow)
• Experience with or strong interest in Generative AI / LLMs (e.g. RAG, embeddings, prompt engineering)
• Solid software engineering mindset (clean code, version control, testing)
• Familiarity with cloud platforms (Azure, AWS, or GCP) and deployment patterns
• Comfort working across the full AI lifecycle: data → model → production
• Curious, pragmatic, and impact-driven mindset

Nice to have

• Experience with MLOps (CI/CD, MLflow, feature stores, monitoring)
• Experience with LLM orchestration frameworks (e.g. LangChain, LlamaIndex)
• Experience in regulated or enterprise environments
• Consulting or client-facing experience

Why join us

• Work on real AI solutions, not demos or slideware
• High ownership and autonomy
• Exposure to both classical ML and cutting-edge GenAI
• Strong focus on quality, responsibility, and long-term impact
• Opportunity to grow into technical lead or solution architect roles