[Hiring] Mid/Senior AI LLM Engineer @RMG Talent

Role Description

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