Machine Learning Engineer (Mid/Senior)

Role overview Build and operate machine learning systems that support personalised cybersecurity learning. The work spans production LLM applications, recommendations, and embedding-based tools, from shaping an initial idea through evaluation and deployment. At senior level, the role also includes technical leadership, mentoring, and setting engineering practices.

Responsibilities - Develop and maintain LLM applications, including retrieval-augmented generation, agent workflows, and evaluation methods. - Improve an AI tutor to provide guidance informed by learner activity and course context. - Build recommendation and personalisation systems for content selection, learning paths, and difficulty adjustment. - Create embedding models and pipelines for semantic search, content similarity, skill mapping, and learner modelling. - Manage the ML lifecycle, including data pipelines, offline evaluation, A/B tests, deployment, monitoring, and iteration. - Work with product and engineering partners to set outcome measures and guide technical choices; at senior level, lead designs and mentor engineers.

Requirements - Three to five years of ML engineering experience for mid-level candidates, or five or more years with end-to-end ML leadership for senior candidates. - Experience shipping LLM products to users, including RAG, prompt and context engineering, and model evaluation. - Practical experience building recommendation or personalisation systems. - Understanding of embeddings, including model selection and adaptation.

Benefits and work setup - Remote work from the UK or approved EU regions. - Annual training budget of £2,500, work equipment budget, and a paid company retreat. - Health insurance where universal coverage is unavailable, enhanced parental leave, and retirement contribution options. - Virtual team lunches and workspace accessories are also covered.