Applied AI Engineer - GenAI & Production ML

Common Sense AI; Vlaanderen; On-site; EUR 65,000 - 90,000; Full time

Job summary

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.

Responsibilities

• 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.

Skills

Data science & ML

Python

Generative AI / LLMs

Cloud platforms (Azure/AWS/GCP)

ML pipelines

Production systems

Stakeholder communication

Tools

LangChain

LlamaIndex

MLflow

CI/CD

Job description

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.