Senior AI / ML Engineer
Fully Remote
£100,000–£120,000 + benefits
About the Role
Our client, a blockchain analytics scale-up, is looking for a Senior AI / ML Engineer to join their expanding team. They’re scaling their AI capabilities and need someone passionate about applying cutting‑edge machine learning and LLM techniques to real‑world crypto data.
You’ll work directly with a Staff AI / ML Engineer who has built advanced ML teams in the past, driving projects that power their platform – used by investors to discover opportunities, perform due diligence, and defend portfolios.
Key Responsibilities
* Designing, implementing, and maintaining AI / ML models to analyse blockchain data at scale.
* Translating complex datasets into insights that inform investment and trading strategies.
* Working with product teams to build AI‑powered features directly into the core platform.
* Staying on top of developments in AI, ML, and blockchain – and experimenting with new techniques.
* Helping to shape best practices and mentor others as the AI function grows.
Your work will focus on delivering high‑value, product‑driven AI features, including :
* Automated wallet and address labelling through AI and NLP.
* NFT and asset price estimation models.
* Advanced analytics to detect patterns and behaviours across blockchain data.
* Integrating LLM‑based capabilities into customer‑facing products.
What We’re Looking For
* 3–6 years of experience in Data Science or ML Engineering.
* Strong Python skills and hands‑on experience building end‑to‑end ML solutions.
* Interest in blockchain, crypto, or fintech (commercial crypto experience a plus).
* Experience with GCP or similar cloud environments.
* Familiarity with modern LLMs or AI APIs.
* Someone who experiments in their spare time, reads papers, and keeps up with the latest in AI.
* Collaborative and proactive, with the ability to thrive in a remote, fast‑paced environment.
Interview Process
* Culture fit interview.
* Technical discussion with the AI Lead.
* Technical test (general DS / ML best practices).
* Final panel interview.
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