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Artificial Intelligence Engineer

Job in City of Edinburgh, Edinburgh, City of Edinburgh Area, EH1, Scotland, UK
Listing for: Digital Waffle
Full Time position
Listed on 2026-02-07
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 70000 - 100000 GBP Yearly GBP 70000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: City of Edinburgh

£70-100k depending on experience

A high-growth SaaS company is hiring a Senior AI Engineer to help build intelligent, mission-critical systems used in highly regulated environments.

The platform applies machine learning and large language models across complex, end-to-end data workflows, solving real-world problems with measurable social impact.

The Role

As a Senior AI Engineer, you’ll design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning outcomes, balancing experimentation with real-world delivery.

What You’ll Be Doing
  • Designing and developing NLP and LLM-driven solutions for complex, real-world use cases
  • Fine-tuning and adapting foundation models using domain-specific data
  • Building evaluation frameworks, prompt testing tools and data preprocessing pipelines
  • Monitoring, optimising and maintaining deployed models for performance, cost and reliability
  • Implementing explainability, fairness and bias-mitigation strategies
  • Collaborating on MLOps pipelines, CI/CD workflows and production deployments
  • Mentoring junior engineers and promoting best practices across the team
  • Staying current with advances in AI, NLP and MLOps to drive continuous improvement
What We’re Looking For
  • Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership
  • Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents)
  • Experience translating research and experimentation into production systems
  • Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management
  • Hands-on experience with Docker and Kubernetes
  • Strong communication skills and experience mentoring or leading others
Nice to Have
  • Experience working in regulated or sensitive domains
  • Exposure to graph-based retrieval techniques
  • Experience with Azure ML and Dev Ops integrations
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