AI Engineer
Solliciteren
Plaats
AntwerpBelgië
be
Contract
Vooltijds, Onbepaalde duurDatum gepubliceerd
2026-03-05Online to:
2026-05-04EUR 15.00 HOUR
AI Engineer
- Common Sense AI
- België
- 5 uren geleden
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
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
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