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
Location and terms: Fully remote within Europe. Start: ASAP. Salary: EUR gross per year. Long-term collaboration with B2B contracting preferred.
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
Required Skills:
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
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