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# Mid/senior ai llm engineer

- **Company:** David Kennedy Recruitment
- **Location:** Amsterdam, Netherlands (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Software Debugging, DevOps, Web Development, Python (Programming Language), Machine Learning, Language Modeling, Performance Tuning, Software Deployment, QLoRA, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Model Validation, HuggingFace
- **Published:** November 11, 2026
- **Apply:** https://nl.talent.com/redirect?id=642670067331040689&source=vacant&utm_medium=xml&utm_campaign=marketing&utm_product=vacantnew_bulk&oapply=org_v2026-11&puid=edaaaddcddaeaddabdd99ddgeddgaddaada9bddd9ddd9ddfbddgaddcbdagaddacdd89dd7bea3addffddgaed2dddgaddgfddgaddgaddg9ddg6ed3gc9bbb9b3bee3ee33def3de93de73dedgdd9gddefddg3ded3dedgddb3ee33de93deg3ee33ee33deg3ee33ee33ee33ee33ee33ee3&pos=5&xml_batch_generation_id=5b9dd352-a7dd-4287-aea1-001bc1dbc663&falcon=1&pid=5a464b205cdf&bpid=b32466055e0036bd4f638bd748e66ebf

## About the Role

* Proven hands-on experience fine-tuning open-weight AI language models and deploying them into production
 * Strong Python programming skills
 * Practical experience with PyTorch and Hugging Face or comparable machine-learning tools
 * Experience with model training techniques such as supervised fine-tuning, LoRA and QLoRA
 * Familiarity with preference-based training techniques such as DPO or GRPO
 * Experience building training datasets and model evaluation frameworks
 * Practical experience with GPU-based training and debugging
 * Ability to analyse model behaviour, troubleshoot issues and demonstrate measurable improvements
 * Experience working with consumer-facing AI products
 * Comfort working with uncensored AI models, explicit adult/NSFW content and sensitive moderation material

## Description

The role focuses on fine-tuning and improving self-hosted large language models that power personalised AI conversations. You will work hands-on with open-weight models, training datasets, evaluation frameworks and GPU-based training, taking model improvements from experimentation through to production deployment., * Train and fine-tune existing AI language models to improve their conversational abilities

 * Prepare and improve training datasets to help models produce more accurate, natural and consistent responses
 * Develop testing methods to measure model quality and identify areas for improvement
 * Improve conversational memory, personality consistency and long-running dialogue
 * Develop multilingual conversational capabilities and interactions involving multiple characters
 * Investigate model failures and optimise training data, prompts and response filters
 * Run model training experiments using GPUs and troubleshoot technical issues
 * Deploy improved models into production, monitor their performance and continue refining them
 * Collaborate with AI engineering, product, web development and DevOps teams