Design, build, and deploy AI systems using NLP and LLMs. Work with large datasets and integrate AI components into the platform. Collaborate with cross-functional teams.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Senior AI Engineer
£60,000 to £70,000 per annum
Fully Remote - UK Wide
Senior AI Engineer
Our UK based client is hiring a Senior AI Engineer to help design, build and deploy AI systems used across its core platform. The organisation works with large, structured datasets and is expanding its AI capability as part of its product roadmap.
This is a fully remote role, and you can be based anywhere in the UK.
The role
You will work across NLP, LLMs and MLOps, developing models and taking them through to production. The position involves both research and engineering delivery, working closely with teams across AI, MLOps, Data Engineering and Product.
What you’ll work on:
- Designing and developing NLP and LLM-based solutions for platform-specific use cases.
- Keeping up to date with developments in AI, NLP and MLOps and identifying relevant tools and techniques.
- Fine-tuning and adapting foundation models using domain-specific data.
- Running analysis on model behaviour and applying explainability and bias-mitigation methods.
- Building tools for evaluation, prompt testing and preprocessing workflows.
- Monitoring and improving model performance, cost efficiency and reliability.
- Working with technical teams to integrate AI components into the wider platform.
- Building and maintaining MLOps pipelines for training, testing and deployment.
- Implementing CI/CD workflows, versioning and rollback processes.
- Supporting and mentoring junior engineers.
Required experience
- Experience as an AI Engineer or ML Engineer with end-to-end model ownership.
- Strong background in NLP and LLMs (transformers, fine-tuning, RAG, agents).
- Ability to translate research into production-ready solutions.
- Experience with retraining workflows and drift monitoring.
- Understanding of explainability, fairness and bias-mitigation.
- Experience defining evaluation metrics for generative models.
- Knowledge of MLOps practices including CI/CD, monitoring, model registry and deployment.
- Hands-on experience with containerisation tools (Docker, Kubernetes).
- Experience mentoring junior engineers.
Preferred experience
- Experience working in regulated or sensitive environments.
- Experience with graph-based retrieval methods.
- Experience working with Azure ML and integrating models into DevOps workflows.
This is a business we have placed multiple very talented Engineers with and they all love working there. They offer excellent flexibility in regards to working conditions with very strong long term career prospects.
If you'd like to learn more about them, then click the link and apply below. Althernatively, you can reach out to Daniel Buttigieg directly.