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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., • 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.

Cloud Engineer // Contract // £375 // Outside IR35 Looking for an AWS cloud engineer for an initial 3 month engagement with strong likelihood of extension. The role is fully remote, outside IR35 and paying £375 a day. Required Skillset: • AWS Infrastructure - compute (Lambda, EC2, ECS / Fargate), • Infrastructure as Code - CloudFormation, • Template validation and linting, • CI/CD pipeline design and implementation It'd also be great if you had any experience with databases & storage and if you had a programming & scripting background then Python or Node.js (for Lambda functions) would be preferred. The intention is to interview before Christmas with a go-live in January.

Job Description: We’re hiring a Trading Infrastructure Engineer to build the core backend systems for a financial trading network — focused on broker connectivity, execution routing, and real-time settlement across synthetic products. This role involves deep integration with broker infrastructure, low-latency order handling, and a sophisticated margin and clearing engine. This is a fully remote 🌍, full time position. Responsibilities • Integrate with broker order flow using FIX APIs and bridge platforms (e.g., PrimeXM, Centroid), • Build internal routing and execution logic across multiple counterparties, • Design and enforce margin and net settlement systems per client, • Connect to institutional LPs and normalize multi-venue pricing data, • Own the reliability and accuracy of high-throughput trade matching infrastructure Requirements • 5+ years experience building backend infrastructure in financial markets, • Direct experience integrating FIX APIs and broker bridges (PrimeXM required), • Experience with CFDs, • Strong programming skills (Python, or similar), • Deep understanding of execution logic, margin enforcement, and post-trade flows Nice to Have • Experience with clearing systems, prime brokers, or liquidity providers, • Exposure to net settlement, per-broker margin models, or matching engines, • Knowledge of institutional custody or collateral management systems • DeliverablesIntegrate with broker order flow using FIX APIs, • Build internal routing and execution logic, • Design margin and net settlement systems, • Connect to institutional LPs and normalize pricing data, • Ensure reliability of trade matching infrastructure