Machine Learning Engineer (hybrid or remote) in London

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we've worked with over 350 global customers to transform their performance through human-centric AI. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we're always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you'll be empowered to envision its most powerful applications, and to make them happen. About the teamIn our Professional and Financial Services Business unit, we bring everything we have learned in more than a decade of Applied AI, and use it to help our clients navigate a rapidly changing landscape. We develop and embed AI solutions which help financial institutions become more efficient, enhance customer experience, and find the commercial upside in uncertain markets. Within the constraints of a highly regulated industry, we see so much opportunity for impactful innovation and are proud to set the gold-standard for marrying technical excellence with safe deployment. About the roleJoin us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse Financial Services clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems. Building and deploying production-grade ML software, tools, and infrastructure. Creating reusable, scalable solutions that accelerate the delivery of ML systems. Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges. Leading technical scoping and architectural decisions to ensure project feasibility and impact. Defining and implementing Faculty's standards for deploying machine learning at scale. Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. AWS, Azure, GCP), including architecture and security. You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scaleYou are comfortable with core ML concepts, including probability, statistics, and common learning techniques. Talent Team Screen (30 mins)Pair Programming Interview (90 mins)System Design Interview (90 mins)Commercial Interview (60 mins)Our Recruitment EthosWe aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. Unlimited Annual Leave PolicyPrivate healthcare and dentalEnhanced parental leaveFamily-Friendly Flexibility & Flexible workingSanctus CoachingHybrid WorkingIf you don't feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.LocationUK - LondonAddressLondon, LondonEmployment TypeFull timeLocation TypeHybridDepartmentProfessional & Financial Services