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Data & AI Engineer – Data Pipelines, ML & GenAI

Differdange, Luxembourg

Build it. Ship it. Run it.

Deltria is a new IT services company, and you'd be one of our first engineers. As a company, we favor quality over quantity: fewer projects, done properly. We're looking for someone who enjoys turning messy data and promising AI ideas into systems that work in production.

No slide decks by default, no politics, no corporate policies that take two days to read, no long approval chains, no "that's not your scope". You'll help pick the tools, set the standards and build the engineering culture with us.

What you'll do

You'll build and run the data and AI solutions of client engagements, working closely with our architects, from the first prototype to production.

  • Build data pipelines. Batch and real-time ingestion, transformation and data modeling, with tests, data quality checks and lineage built in.
  • Bring AI to production. Traditional ML (forecasting, classification, anomaly detection, NLP) as well as GenAI (LLM-based applications, RAG, agents): train, evaluate, deploy and monitor models that deliver value, not demos.
  • Run anywhere it makes sense. On hyperscalers (AWS, Azure, Google Cloud), on sovereign and European clouds (Scaleway, OVHcloud, STACKIT, Clever Cloud, S3NS) and on-premises, including GPU infrastructure and self-hosted open-weight models.
  • Engineer it properly. Version control, code reviews, automated tests, CI/CD, DataOps and MLOps, observability. Prototype fast, then harden.
  • Work with clients. Understand their data and their problem, challenge assumptions, and explain results and limits in plain words.
  • Help shape Deltria. Share what you learn, build reusable components, and help define how we work.

What you bring

What you've built matters more than your title. Here's what we're looking for.

  • 3+ years in data, ML or software engineering, with solutions you built running in production.
  • A major and a minor: strong skills in either AI or data engineering, and solid working knowledge of the other.
  • Python is a must: clean, tested, production-grade Python, from pipelines to models to APIs. Strong SQL too.
  • AI beyond GenAI: hands-on with traditional ML (scikit-learn, XGBoost, PyTorch or similar): feature engineering, training, evaluation, monitoring. LLM-based work on top is a plus.
  • Solid data engineering: data modeling, orchestration, batch and streaming, data quality, lineage and metadata management.
  • You build with AI assistants: you use coding assistants and agents every day and keep quality, testing and security under control.
  • Comfortable with infrastructure: Docker, Kubernetes basics, Git and CI/CD; at least one cloud provider, and no fear of on-premises.
  • Clear communication in English: in writing and with clients.

Bonus points

  • Cloud or data certifications
  • Serving open-weight models: vLLM, Ollama, GPUs on Kubernetes
  • Vector databases and search: pgvector or OpenSearch
  • Open-source data tooling: Iceberg, OpenMetadata, Kafka, dbt or Airflow
  • Data platforms: Databricks, Snowflake or Microsoft Fabric
  • MLOps and LLMOps tooling: MLflow, Kubeflow, LiteLLM or similar
  • Large environments: public sector, European institutions, finance
  • Consulting or IT services experience

Why Deltria

  • Impact from day one. You join at the start; your choices on stack, practices and culture will last.
  • Short decision paths. No layers of management between an idea and trying it.
  • Room to grow. As Deltria grows, so does your scope: toward senior engineer, tech lead or architect.
  • Time and budget to learn. Certifications, conferences and room to try new tech.
  • Flexible package. Car, meal vouchers, pension and other benefits.

The practical bits


Location

Luxembourg/Belgium, hybrid, with time on client sites when useful


Contract

Permanent contract (CDI), full-time


Start

ASAP


Languages

English required; French or German a plus