[Hiring] Mid/Senior AI LLM Engineer @David Kennedy Recruitment

Role 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.

Qualifications

• Proven hands-on experience fine-tuning open-weight LLMs and deploying them into production
• Strong Python programming skills
• Practical experience with PyTorch and Hugging Face
• Hands-on experience with GPU-based model training and debugging
• Experience with supervised fine-tuning and parameter-efficient fine-tuning techniques, including LoRA or QLoRA
• Familiarity with preference optimisation techniques such as DPO or GRPO
• Ability to independently build training datasets and model evaluation frameworks
• Experience working with consumer-facing AI products
• Comfort working with uncensored AI models, explicit adult/NSFW content and sensitive moderation material
• Ability to diagnose model behaviour issues and translate findings into measurable improvements

Requirements

• Fine-tune open-weight large language models using techniques such as supervised fine-tuning (SFT), LoRA, QLoRA, DPO and GRPO
• Build and maintain training datasets and model evaluation frameworks
• Improve conversational memory, personality consistency and long-running dialogue quality
• Develop multilingual conversational capabilities and group interaction behaviours
• Diagnose model failures and optimise training data, prompts and classifiers
• Run GPU-based training experiments, debug issues and assess model performance
• Deploy improved models into production, measure results and iterate on performance
• Collaborate with the LLM Tech Lead, CTO, Product, Web and DevOps teams to deliver model improvements

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
• And many more!!!