Machine Learning Engineer (hybrid or remote) in London

Machine Learning EngineerLocation: LondonSalary: 95,000-120,000Contract: On site, 3 days a weekA new software venture built inside an established global provider of analytical and research services to the private capital industry is hiring Machine Learning Engineers to build the models, agents and evaluation systems that investment professionals rely on to analyse data, work with documents and automate research. You'll join the UK core team of around thirty people, working in Python on production ML and LLM systems that sit behind data-dense enterprise products. THE ROLEYou'll report to the Head of Engineering and own the machine learning layer of the platform, from the first prototype through to a monitored production service. The work combines applied LLM engineering with the rigour that high-stakes financial workflows demand.Part of an engineering cohort being hired across machine learning, front-end and back-end.WHAT YOU'LL BE DOINGYour remit spans the models and agents, the data and retrieval layer, the evaluation framework and the production platform.Design, build and ship LLM-powered features and multi-step agent workflows in Python, from prototype to production.Build document intelligence pipelines that extract, structure and reason over long, messy financial documents such as filings, decks, models and data rooms.Implement guardrails, confidence signalling and safe failure behaviour, and work with front-end colleagues to expose approvals, tool calls and partial progress to users.Fine-tune, prompt-engineer and benchmark models, and make considered decisions between hosted foundation models, open-weight models and classical ML on cost, latency and quality.Build and operate ML services and APIs with authentication, role-based access and tenant isolation, so client data is never mixed across tenants.Own MLOps in production: experiment tracking, model and prompt versioning, monitoring, drift detection, cost and latency management, and incident response.Write unit, integration and evaluation tests, and ship through Jenkins and SonarQube pipelines to AWS.Work with back-end and front-end engineers and with domain experts in private capital to turn real analyst workflows into reliable products.WHAT WE'RE LOOKING FOR5+ years in machine learning or software engineering, with production ML experience and strong Python.Hands-on experience shipping LLM-based or NLP systems to real users, including RAG, agents and tool use, and the ability to explain the design and trade-off decisions behind them.Strong grounding in the ML stack, such as PyTorch, scikit-learn, Hugging Face and vector databases, alongside sound software engineering practice.Experience deploying and monitoring models on cloud infrastructure, ideally AWS, with Git, CI/CD and containerisation.Experience building SaaS or multi-tenant products, with a working understanding of data security, access control and privacy.Daily use of AI coding tools such as Cursor or Claude Code, and a considered view of where they help.A degree in computer science, engineering, mathematics, statistics or a related field, or equivalent experience. A postgraduate degree is valued but not required.NICE TO HAVEExperience building agentic products, including orchestration, memory, tool calling and human-in-the-loop controls.Document understanding, OCR and table extraction on complex financial documents.Fine-tuning or distillation of language models, and inference optimisation.Experience with financial, investment or other regulated-industry data.The goal is to build the foundations of an enterprise-grade technology platform serving a multi-billion dollar serviceable market, and to share in that growth.A production ML or LLM system you shipped: the architecture, data and cost decisions.An evaluation approach you designed to measure or improve quality, and what it revealed.In office 3 days a week.To understand more about what we do with your data please review our privacy policy in the privacy section of the Oscar website.