Open role
Mid/Senior AI LLM Engineer – Remote (Europe)
This is a remote position.
About the role We are looking for a hands-on Mid/Senior AI LLM Engineer to improve the self-hosted large language models that power consumer-facing conversational AI products. The role centres on fine-tuning open-weight LLMs, building datasets and evaluations, debugging GPU training runs and taking measurable improvements into production. This is a specialist post-training engineering position: you will own the full loop from data and training to evaluation and deployment. It is not an AI research role, nor a role connecting to third-party chatbot APIs. Key responsibilities- Fine-tune and post-train open-weight language models and deploy them into production
- Build training datasets and evaluate model performance independently
- Work on long-context consistency, personalization, multilingual quality, group chat and better model evaluation
- Debug and optimise GPU training workloads
- Measure and ship improvements for consumer-facing conversational AI products
- Contribute to ongoing moderation and safety evaluations
Requirements
- Hands-on experience fine-tuning open-weight language models and deploying them into production
- Strong Python skills
- Practical experience with PyTorch and Hugging Face
- Experience with supervised fine-tuning and LoRA/QLoRA
- Familiarity with preference-based training methods such as DPO or GRPO
- Practical GPU training and debugging experience
- Ability to build training datasets and evaluate model performance independently
- Experience working on consumer-facing AI products
- Comfortable working with unrestricted AI models and adult content as part of the product, including sensitive moderation material
- A hands-on engineering profile - not an AI researcher and not a developer who simply connects to ChatGPT APIs
Benefits
- Fully remote working within Europe
- Long-term collaboration, with B2B contracting preferred
- 20 working days of paid leave
- $100 monthly health insurance allowance
- Equipment budget
- Access to AI development tools
- Learning and development support
- Annual team gathering
- Opportunity to work on self-hosted LLMs powering consumer-facing AI products
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