Senior AI Engineer
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.