LLM engineer

Computer Futures

Antwerpen

Sur place

EUR 90 000 - 120 000

Plein temps

Il y a 10 jours

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Résumé du poste

Computer Futures in Belgium is seeking an experienced LLM Engineer to design, fine-tune, and deploy large language models that automate complex processes in a manufacturing AI environment.

You will collaborate with software engineers, data scientists, and business stakeholders to translate requirements into scalable AI applications, build proof-of-concepts, and integrate AI capabilities across systems using modern tooling.

Qualifications

  • Master's degree in Computer Science or related field.
  • 7+ years of relevant industry experience.
  • Strong experience with NLP, LLMs, and transformer architectures.
  • Proficiency in Python and/or C++.
  • Hands-on with Hugging Face, PyTorch, TensorFlow, scikit-learn, spaCy.
  • Experience with LangChain, AI workflows, and AI app development.
  • Fluent in Dutch and English.
  • Excellent communication with technical and business stakeholders.

Responsabilités

  • Develop, fine-tune, and deploy production-ready LLMs.
  • Design NLP solutions delivering measurable business impact.
  • Translate business requirements into scalable AI architectures.
  • Build AI agents, skills, and integrations for platforms.
  • Develop MCP servers enabling secure data access.
  • Lead PoC initiatives from ideation to implementation.
  • Collaborate with cross-functional teams to embed AI capabilities.
  • Contribute to AI-assisted development workflows with Copilot and Claude Code.

Connaissances

NLP & LLMs
Transformer models
Python
C++
LangChain
AI workflows
Communication
Dutch & English

Formation

Master's degree in Computer Science

Outils

Hugging Face
PyTorch
TensorFlow
scikit-learn
spaCy

Description du poste

Are you passionate about transforming cutting-edge AI research into real-world business value?

We're looking for an experienced LLM Engineer to join an innovative AI and Intelligent Systems team driving digital transformation within a highly automated, technology-driven manufacturing environment.

Your Impact

In this role, you'll design, fine-tune, and deploy large language models that automate complex business processes and support critical operations. You'll collaborate closely with stakeholders, software engineers, and data specialists to identify high-value opportunities, build proof of concepts, and scale successful solutions into enterprise-grade applications.

Key Responsibilities
  • Develop, fine-tune, test, and optimize LLMs for production environments
  • Design and implement NLP solutions that deliver measurable business impact
  • Translate business requirements into scalable AI, data, and software architectures
  • Build AI agents, skills, and integrations for modern AI platforms
  • Develop MCP servers enabling secure data access and controlled automation
  • Lead proof-of-concept initiatives from ideation through implementation
  • Collaborate with cross-functional teams to embed AI capabilities into existing systems
  • Contribute to next-generation AI-assisted development workflows using tools such as GitHub Copilot and Claude Code
What We’re Looking For
  • Master's degree in Computer Science or a related field
  • 7+ years of relevant industry experience
  • Strong experience with NLP, LLMs, and transformer-based architectures
  • Proficiency in Python and/or C++
  • Hands-on expertise with Hugging Face, PyTorch, TensorFlow, scikit-learn, spaCy, or similar frameworks
  • Experience with LangChain, agentic workflows, and AI application development
  • Familiarity with AI-assisted development tools and modern software engineering practices
  • Excellent communication skills and the ability to engage with both technical and business stakeholders
  • Fluent in Dutch and English
What Makes This Opportunity Unique

This position offers the chance to work at the forefront of applied AI, developing solutions that move beyond experimentation and create tangible value at scale. You'll be part of a forward-thinking team shaping AI strategy, driving adoption, and building innovative systems that define the future of intelligent operations.

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