Principal Data Scientist (Fine-tuning & Model Optimisation

Position: Principal Data Scientist (Fine-tuning & Model Optimisation)
Principal Data Scientist (Fine-tuning & model optimisation) - AI Models Lead

Hybrid:
Remote

Paying up to £130,000 + bens

Permanent

Experis are delighted to be partnering with a highly successful and growing software organisation as they invest heavily in building a cutting-edge AI capability at the heart of their product suite.

We are supporting them in the search for an AI Models Lead, a key foundational hire who will own the development, fine-tuning, and production delivery of domain-specific AI models within a large-scale programme.

This is a rare opportunity to join at an early stage and build a fine-tuning capability from first principles, shaping how AI models are developed, evaluated, and deployed in real-world, regulated environments. Looking for someone who has moved beyond prompt engineering and RAG into genuine model adaptation, evaluation, optimisation and fine-tuning.

What You'll Be Doing

Designing and leading the end-to-end model fine-tuning strategy, such as SFT, LoRA / QLoRA, and optimisation approaches
Selecting and evaluating base models (e.g. Mistral, Qwen, Phi, Falcon) based on performance, cost, and use case
Defining evaluation frameworks and standards to ensure models meet production-grade quality and reliability
Building and scaling a suite of fine-tuned models to support multiple product use cases
Owning experiment design and reproducibility, including tracking, benchmarking, and iteration cycles
Working closely with data, domain and product teams to translate real-world requirements into model behaviour
Leading, mentoring, and growing a team of ML Engineers while remaining hands-on technically
Driving models through to production environments, ensuring robustness, scalability, and performance

Experience Required

Proven experience fine-tuning machine learning / LLM models in production environments
Strong track record of deploying AI models at scale and understanding real-world failure modes
Hands-on experience with Generative AI / LLM architectures and frameworks
Strong Python engineering capability and familiarity with ML tooling (e.g. Hugging Face, PEFT, TRL, W&B)
Experience working in cloud environments (AWS preferred)
Ability to operate as a player-coach, combining deep technical expertise with leadership
Pragmatic mindset, comfortable working in ambiguous, evolving environments
Excellent communication skills, with the ability to engage senior stakeholders and influence direction

Why Join

Opportunity to build and shape a core AI capability from the ground up
Work on real-world AI use cases where accuracy and trust genuinely matter
Highly visible role with direct exposure to senior leadership and strategic initiatives
Join a business making significant long-term investment in AI-driven innovation

If you're interested in learning more, please reach out to Jacob Ferdinand at

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