Location- Ruddington, Nottinghamshire

Level - Team Leader/Professional

Department - Product R&D

Working Pattern - Remote unless based locally

Benefits - Benefits at Ideagen

Salary - To be discussed at next stage

• Leading and developing the AI Models Team, setting engineering standards, mentoring engineers, and establishing a strong technical culture
• Designing and owning the end-to-end fine-tuning methodology, including training configuration, evaluation gates, reproducibility standards, and promotion criteria
• Making base model selection decisions across foundation model families, balancing capability, cost, and inference constraints for different domain tasks
• Owning LoRA and QLoRA adaptation strategy, including configuration choices, training compute decisions, and compatibility with the inference layer
• Applying supervised fine-tuning and preference optimisation techniques to domain-specific classification and compliance problems
• Building robust evaluation frameworks with domain experts to assess whether models are performing correctly in real EHS, Quality, and GRC use cases
• Leading dataset design and construction, defining labelling standards and ensuring training data is versioned, auditable, and reproducible
• Owning production training and adapter lifecycle management, from large-scale training jobs through to registry promotion and release readiness

• You have a proven track record of fine-tuning language models that serve real production traffic, with a strong understanding of operational failure modes
• Deep practical experience with LoRA and QLoRA, and clear intuition for the trade-offs between quality, compute cost, and inference performance
• Hands-on experience applying alignment techniques such as supervised fine-tuning and preference optimisation to real-world problems
• Strong tooling fluency with modern ML frameworks and experimentation platforms, including debugging and scaling training pipelines
• High-quality Python engineering skills, with emphasis on readable, testable, and maintainable training and evaluation code
• Experience leading or mentoring engineers in a technical ML environment, with a people-first approach to leadership
• Comfortable working with subject-matter experts to define “what good looks like” when evaluation requires real domain judgment
• Background or interest in regulated domains such as EHS, quality management, healthcare, or financial services is advantageous

About Ideagen

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