Machine Learning Engineer (Mid/Senior) (AI)

Location: Fully remote within the UK or approved EU regions; the role is listed as UK & Europe Remote / Hybrid.

Company

hirify.global is an online cyber security training platform serving more than 9 million learners and businesses training their teams.

What you will do

• Design, build, and operate production LLM applications, including RAG pipelines, agentic workflows, and evaluation frameworks.
• Evolve Echo, the AI tutor, to provide context-aware and personalised guidance across labs and challenges.
• Build recommendation and personalisation systems for next-best content, learning paths, and difficulty adaptation.
• Develop embedding models and pipelines for semantic search, content similarity, skill mapping, and learner modelling.
• Own the ML lifecycle across data pipelines, offline evaluation, A/B testing, deployment, monitoring, and iteration.
• Partner with product on success metrics; at senior level, lead technical design, mentor engineers, and shape ML engineering standards.

Requirements

• Mid-level candidates: 3–5 years of ML engineering experience; senior candidates: 5+ years and a track record of leading ML systems end to end.
• Hands-on experience shipping LLM-based products to real users, including RAG, prompt and context engineering, and LLM evaluation.
• Experience building recommendation or personalisation systems at scale.
• Understanding of embeddings, including model selection, fine-tuning or adaptation, vector search, and retrieval quality.
• Strong Python and software engineering fundamentals, including testing, code review, CI/CD, and secure coding.
• Experience deploying and operating ML services with Docker, Kubernetes, REST APIs, and microservices.
• Comfort with SQL and large-scale data processing.
• Ability to design experiments and reason about offline and online metrics, with clear communication across technical and non-technical stakeholders.

Nice to have

• Cyber security background or genuine interest, including CTFs, homelabs, security roles, or hirify.global usage.
• Experience fine-tuning and efficiently serving open-source LLMs using LoRA/QLoRA, SFT, preference tuning, vLLM, or quantisation.
• Experience with vector databases such as pgvector, Qdrant, Weaviate, or Pinecone.
• Learner modelling, knowledge tracing, or EdTech experience.
• PyTorch, Hugging Face, scikit-learn, and MLOps tooling such as MLflow, feature stores, or model monitoring.
• Experience with agent frameworks, tool use, or LLM guardrails.

Culture & Benefits

• Small, high-autonomy team with direct impact on millions of learners and global enterprises.
• Candid feedback culture focused on rapid execution, high trust, and ownership.
• Profitable, fast-growing, self-sustaining early-stage scale-up.
• 100% remote work within the UK or approved EU regions.
• MacBook Pro, workspace accessories budget, £2,500 annual training budget, paid annual retreat, health insurance where applicable, enhanced parental leave, and pension / 401(k) contribution options.

Hiring process

• Introductory chat with a Talent Partner, followed by a technical and experience interview with the Head of Engineering.
• Take-home AI-assisted technical assessment and follow-up with engineers.
• Founders interview covering culture and operating alignment.