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David Kennedy Recruitment

Mid/Senior AI LLM Engineer

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AI Summary

The role involves fine-tuning and improving self-hosted large language models to enhance conversational quality and personality consistency. You will manage the full lifecycle of model development, from training and debugging on GPUs to production deployment and performance evaluation.

David Kennedy Recruitment is working with a company developing AI-powered conversational products, that is seeking to onboard a Mid/Senior AI LLM Engineer to join their team remotely.

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.

Position: Mid/Senior AI LLM Engineer

Location: Europe, Remote

Employment type:  B2B engagement

DUTIES AND RESPONSIBILITIES:

  • 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

REQUIREMENTS:

  • 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

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!!!

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