Machine Learning Engineer

Job Title: Machine Learning Engineer – Finance Location: London (2 days on-site) Salary: £60,000 – £80,000 + benefits About UsOur client is a fast-growing FinTech startup redefining how mid-sized enterprises manage liquidity, credit, and cross-border finance. Since 2020, they’ve grown to a 60-person team across the UK, closed our Series B, and are backed by top-tier investors including Notion and Accel.At the core of our platform is intelligent decision-making at scale… and that’s where you come in. We’re now looking for a Machine Learning Engineer who’s ready to take ownership of production-level models that directly impact risk, underwriting, and transaction workflows.What You’ll Do:Design, build, and deploy ML models for real-time credit risk scoring, fraud detection, and dynamic pricingArchitect and implement end-to-end ML pipelines (from data ingestion and feature engineering to monitoring and retraining)Collaborate with product, engineering, and data teams to identify use cases, develop models, and integrate into our core platformExperiment with and apply state-of-the-art techniques in NLP, time series, and anomaly detectionOwn model evaluation, explainability, and monitoring frameworks in productionStay up to date with developments in the ML/AI ecosystem and bring fresh ideas to the tableWhat we’re looking for:Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow, or XGBoostHands-on experience building and deploying ML models into production environmentsFamiliarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow)Experience working with structured data (credit, payments, customer behaviour) and applying feature engineering at scaleUnderstanding of model performance metrics, calibration, A/B testing, and monitoring in production systemsExperience with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AIProficiency in SQL and working knowledge of distributed computing tools like Spark or DaskNice to Have:Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classificationFamiliarity with Graph ML (e.g., for customer network analysis or fraud detection)Exposure to finance, credit risk modelling, or regulated environmentsStrong software engineering fundamentals, version control, CI/CD, testingPrevious startup experience or entrepreneurial mindsetWhat We Offer:A chance to work on real-world ML problems that power decisions across millions in daily transactionsCompetitive salary and meaningful equity25 days holiday + bank holidaysPrivate healthcare & life insuranceGenerous learning budget + conference supportAn open, inclusive culture where experimentation is encouraged and your voice will be heard