Machine Learning Engineer (various levels), AI - London

About the Opportunity Our client is a well-capitalised, early-stage technology company developing an advanced AI-driven product for consumers. The engineering challenge is significant: the system must perform complex, multi-step reasoning, maintain context over extended interactions, and operate reliably in production despite the inherent unpredictability of large models. The organisation is deliberately lean - a small group of senior, high-calibre engineers who move quickly, make decisions collectively, and hold a high bar for both quality and pace. The mission is to deliver a product experience that feels genuinely different from what's currently on the market. The Roles Our client is looking to hire multiple profiles into their ML Technical staff. As a Member of Technical Staff, Machine Learning, you will build core ML components and work directly on production systems from day one - gaining first-hand exposure to how large-scale ML behaves outside a research setting. This role suits engineers who want to build strong systems judgement through shipping, debugging, and iterating on real-world ML, alongside more senior colleagues. Focus Areas - Build and improve ML components spanning data, training, evaluation, and inference - Fine-tune and adapt models as part of larger production systems - Implement evaluation and testing frameworks to understand model behaviour - Contribute to data pipelines covering both real-world and synthetic data - Debug model issues, performance problems, and production incidents - Ship improvements iteratively, guided by real user feedback - Work closely with senior ML engineers and product teams - Operate comfortably within the constraints of a live production system - latency, cost, reliability, and safety all matter simultaneously What Good Looks Like in This Role - Production ML models meet expected accuracy, latency, and reliability targets - Production issues are identified quickly, debugged effectively, and resolved at the root cause - Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable - Works effectively across engineering, product, and research to deliver reliable ML-powered features - Improvements to models and systems are driven by real-world signals and measurable outcomes Technical Environment - Python - PyTorch / JAX - Production ML systems running on GPU infrastructure Candidate Profile - Strong foundations in machine learning and modern neural network architectures - Some hands-on experience training, fine-tuning, or deploying ML models - Comfortable writing production-quality code and picking up new tools quickly - Curious, coachable, and keen to learn from real systems in production - Able to work through ambiguity with guidance, growing ownership over time - A natural bias toward shipping, iteration, and continuous improvement To apply or discuss this role further please send your CV to Don Fletcher via don.fletcher@ap-executive.com AP Executive are working with a well capitalised early stage AI firm looking to expand their ML Team. AP Group is acting as an introductory service in relation to this vacancy. By submitting your CV for consideration, you are consenting to its retention for the purpose of securing you work. Any information you provide to AP Group and its subsidiaries will be subject to the protection of Data Protection Laws, our policy for which can be found at https://www.apgroupglobal.com/privacy-notice/