Machine Learning Engineer – Mid/Senior

Job not on LinkedIn

🔥 1 minute ago

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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TryHackMe

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

🔒 Cybersecurity

📚 Education

☁️ SaaS

Cybersecurity • Education • SaaS

TryHackMe is an online learning platform that makes learning and teaching cybersecurity accessible and practical through prebuilt courses, cloud-hosted virtual machines (VMs), and hands-on labs designed for CTFs, workshops, assessments, and training. Launched in 2018, the platform emphasizes practical, deployable environments so users can avoid local VM configuration, and it serves millions of learners while supporting both individual and organizational training needs.

📋 Description

• Design, build and run production LLM applications, including RAG pipelines, agentic workflows and evaluation frameworks, focusing on quality, latency and cost • Evolve Echo, TryHackMe’s AI tutor, to provide context-aware, personalised guidance through labs and challenges • Build and improve 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 full ML lifecycle: data pipelines, offline evaluation, A/B testing, deployment, monitoring and iteration • Make build-vs-buy decisions across open-source and hosted models, and decide when to prompt, fine-tune or train • Partner with product to define success metrics and connect model improvements to learner outcomes and engagement • At senior level, lead technical design for ML initiatives, mentor engineers and shape the ML platform and standards • Work closely with product squads, the data team and engineering to take ideas through measurable production results

🎯 Requirements

• Mid: 3-5 years in ML engineering • Senior: 5+ years, with a track record of leading ML systems end to end • Hands-on experience shipping LLM-based products to real users • Practical knowledge of RAG, prompt and context engineering, and LLM evaluation • Practical experience building recommendation or personalisation systems at scale • Solid understanding of embeddings, including model selection, fine-tuning or adaptation, vector search and retrieval quality • Strong Python and software engineering fundamentals: 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 metrics, both offline and online • Clear communication with both technical and non-technical stakeholders • Cyber security background or genuine interest, such as CTFs, homelabs, a security role, or being a TryHackMe user yourself • Experience fine-tuning open-source LLMs (LoRA/QLoRA, SFT, preference tuning) and serving them efficiently (vLLM, quantisation) • Vector databases (pgvector, Qdrant, Weaviate, Pinecone or similar) • Learner modelling, knowledge tracing or EdTech experience • PyTorch, Hugging Face and scikit-learn; MLOps tooling such as MLflow, feature stores and model monitoring • Experience with agent frameworks and tool-use or LLM guardrails

🏖️ Benefits

• 100% Remote: Work from anywhere within the UK or approved EU regions • Latest MacBook Pro + budget for any workspace accessories you need • Exclusive TryHackMe gear • £2,500 annual training budget for certifications, courses, and conferences • Fully paid annual company-wide retreat • Covered during recurring virtual team lunches • Health Insurance provided in regions without universal coverage • Enhanced maternity and paternity packages • Company contribution options for retirement savings via Pension / 401(k)

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