Senior ML Engineer: LLMs, RAG & Personalisation (Remote)

TryHackMe; United States; Remote; USD 119,000 - 185,000; Full time

Benefits offered by this job

Remote work

Health insurance

Training budget

Company retreat

Pension plan

Job summary

TryHackMe, the fastest-growing online cybersecurity training platform, is hiring a Mid/Senior Machine Learning Engineer. Design, build and own production ML systems that shape how millions learn through LLM-powered experiences, recommendations and embedding-based tooling.

You will lead ML initiatives, mentor engineers, and set technical direction while collaborating with product, data and engineering teams across remote UK/EU work locations.

Qualifications

• Hands-on experience shipping LLM-based products to real users.
• Experience with RAG, prompt and context engineering.
• Experience building recommender or personalization systems at scale.
• Solid understanding of embeddings, vector search and retrieval quality.
• Strong Python and software engineering fundamentals.

Responsibilities

• Design, build and run LLM applications in production, focusing on quality, latency and cost.
• Evolve Echo, the AI tutor, to provide context-aware, personalized guidance.
• Build and improve recommendation and personalization systems based on learner behavior.
• Develop embedding models and pipelines for semantic search and learner modeling.
• Own the full ML lifecycle: data pipelines, evaluation, deployment, monitoring and iteration.
• Make build-vs-buy decisions across open-source and hosted models.
• Define success metrics with product and tie model improvements to learner outcomes.

Skills

LLM systems

RAG pipelines

Prompt engineering

Embeddings

PyTorch

Docker

Kubernetes

Python

Vector databases

MLOps

Tools

REST APIs

Microservices

Weaviate/pgvector

Job description

TryHackMe, the fastest-growing online cybersecurity training platform, is hiring a Mid/Senior Machine Learning Engineer. Design, build and own production ML systems that shape how millions learn through LLM-powered experiences, recommendations and embedding-based tooling.

You will lead ML initiatives, mentor engineers, and set technical direction while collaborating with product, data and engineering teams across remote UK/EU work locations.