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Principal Data Scientist (Fine-tuning & Model Optimisation)

ExperisUnited Kingdom🇬🇧United KingdomPosted 12 Aug 2026

Why This Role Stands Out

This Principal Data Scientist role offers a unique opportunity to build and lead an AI fine-tuning capability from the ground up within a growing software organization, with a competitive salary of up to £130,000 plus benefits. You will thrive here if you have a passion for genuine model adaptation and optimization, seeking to shape the future of AI models in regulated environments. Embrace the flexibility of a hybrid work model and make a significant impact on cutting-edge AI development.

Quick Overview

Work Type
Hybrid
Schedule
Full Time
Level
Leader

Job Description

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. HuggingFace, 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

If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.

Skills

AWS
Machine Learning
Generative AI
LLM
Python

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