Head of Data Science

Principle AI Data Scientist (LLM Architecture)

A leading UK Managed Service Provider is launching a new applied AI practice for enterprise clients. We’re hiring a Principle AI Data Scientist to design LLM solutions, defend the choices behind them, and turn deep model knowledge into results clients will pay for.

This is not a back office research role. You’ll work directly with client engineering leads and senior technical stakeholders, from the first whiteboard session to production deployment.

Why this role stands out

• Real architect-level ownership. You’ll shape how LLMs are fine-tuned, evaluated and deployed for named enterprise accounts. You won’t be working through someone else’s backlog.
• A ground-floor opportunity. You’ll help build a new AI practice inside an established, commercially stable business, rather than competing for attention at a crowded AI startup.
• Science that stays sharp. You’ll join a small, technically elite team where “customer-facing” doesn’t mean watering down the science. It means being trusted to represent it.
• Visible impact. The people making buying and build decisions will see and value your technical depth.

What you’ll be doing

• Acting as the main technical point of contact for enterprise clients on LLM projects, from scoping through to deployment
• Designing LLM training, fine-tuning and evaluation pipelines for each client’s use case and data environment
• Turning unclear client requirements into concrete technical architectures and delivery plans
• Leading technical discovery and whiteboard sessions with client engineering and data science teams
• Owning model performance, evaluation methodology and responsible deployment recommendations
• Working with sales, account management and delivery to make sure every design is technically sound and can be delivered commercially within a managed services model

What you’ll bring

• 5+ years in applied data science or ML engineering, with hands-on LLM training or fine-tuning experience beyond API use
• Practical experience with transformer architectures, LLM pre-training or fine-tuning workflows, and modern ML frameworks such as PyTorch or Hugging Face
• A strong grounding in evaluation methodology, the trade-offs between RAG and fine-tuning, and production ML deployment patterns
• Confidence and credibility with senior technical stakeholders. You’re comfortable with pushback in live technical discussions and equally at home in a boardroom or a terminal.

Nice to have

• Experience with distributed training infrastructure (multi-GPU, multi-node)
• A background in pre-sales, solutions architecture or consulting
• Familiarity with model safety, alignment or responsible AI evaluation frameworks
• Experience in an MSP, systems integrator or managed services environment

Interested?

If you want your technical depth to be seen, trusted and valued by the people making the decisions, we’d love to hear from you.

Location: London

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