Client-Facing AI Data Scientist & LLM Architect

Hamilton Barnes ?; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Hamilton Barnes is looking for a Customer-Facing AI Data Scientist (LLM Architecture) to join a growing MSP practice in London. You will sit with enterprise clients, shaping LLM deployments, evaluating training and fine-tuning strategies, and ensuring commercial viability of AI solutions.

You will work at the intersection of deep technical LLM expertise and client delivery, translating complex model concepts into actionable architectures and delivery plans for named accounts.

Qualifications

• 5+ years in applied data science or ML engineering with direct exposure to LLM training or fine-tuning at a technical level.
• Hands-on experience with transformer architectures and modern ML frameworks (PyTorch, Hugging Face, or equivalent).
• Strong grounding in evaluation methodologies, RAG and fine-tuning trade-offs, and production ML deployment patterns.
• Confident and credible in front of senior technical stakeholders and able to defend design decisions in live discussions.

Responsibilities

• Act as the primary technical point of contact for enterprise clients on LLM-based engagements, from scoping through deployment.
• Design and architect LLM training, fine-tuning, and evaluation pipelines tailored to client use cases.
• Translate client requirements into concrete technical architectures and delivery plans.
• Lead discovery sessions with client engineering and data science teams.
• Own model performance, evaluation methodology, and deployment recommendations for client-facing solutions.
• Collaborate with sales and delivery teams to ensure architectural decisions are sound and commercially deliverable.

Skills

LLM training

Transformer architectures

PyTorch/Hugging Face

Stakeholder communication

Job description

Hamilton Barnes is looking for a Customer-Facing AI Data Scientist (LLM Architecture) to join a growing MSP practice in London. You will sit with enterprise clients, shaping LLM deployments, evaluating training and fine-tuning strategies, and ensuring commercial viability of AI solutions.

You will work at the intersection of deep technical LLM expertise and client delivery, translating complex model concepts into actionable architectures and delivery plans for named accounts.