Senior Machine Learning Engineer

London | Hybrid/Remote | £70,000 - £90,000 + stock options + Benefits

Company Overview

We’re a fast-growing FinTech building fairer and smarter lending solutions. Using advanced machine learning and rich financial data, we create credit products that improve outcomes for individuals and small businesses. Our mission is to make lending transparent, responsible, and accessible—and our models are at the heart of how we achieve this.

Joining us means you’ll be part of a collaborative, hands-on team where your work directly contributes to how we assess and manage risk.

The Role

As a Senior Machine Learning Engineer, you’ll take technical ownership of our credit risk model suite — iterating, optimising, and deploying production-ready ML systems that drive real-world impact. You’ll remain hands-on in design and experimentation while mentoring 1–2 junior ML engineers.

You’ll collaborate closely with credit analysts, data scientists, and the wider engineering team to ensure our models are accurate, explainable, and seamlessly integrated into our lending platform.

What You’ll Do

• Lead the design, training, and optimisation of credit risk and behavioural models using Python and frameworks such as XGBoost and scikit-learn.
• Responsible for creating proprietary data enrichment algorithms.
• Guide the evolution toward a self-learning model framework, improving automation and adaptability over time.
• Design and oversee feature testing and evaluation to enhance predictive performance and interpretability.
• Use BigQuery and GCP tools (including CloudRun) to manage and process large-scale datasets efficiently.
• Ensure models are explainable and compliant, collaborating with credit and risk teams to interpret outcomes.
• Mentor junior ML engineers through code reviews, technical guidance, and project planning.
• Work with software engineers to productionise models (deployment and pipelines handled by the engineering team).
• Stay ahead of emerging ML techniques and bring new ideas to improve scalability, performance, and transparency.

What We’re Looking For

• 4+ years of hands-on experience in applied machine learning (preferably in financial services or another regulated domain).
• Proven ability to design, train, and evaluate models using Python, XGBoost, and related ML frameworks.
• Strong experience with SQL and BigQuery; familiarity with GCP infrastructure.
• Comfortable working end-to-end from data exploration through validation and interpretation.
• Understanding of explainable AI and model governance practices.
• Exposure to model monitoring and drift detection frameworks.
• Ability to guide and mentor junior engineers while remaining deeply hands-on.
• Strong communicator who can bridge technical and non-technical discussions with credit, risk, and leadership teams.

Nice to Have

• Experience with MLOps tooling (e.g., MLflow, Airflow, Vertex AI, or similar).
• Familiarity with real-time decisioning systems or lending analytics.

What We Offer

• Ownership of the ML roadmap for a growing fintech with proven traction.
• Opportunity to shape team direction while staying close to the code.
• Collaborative, fast-paced culture focused on experimentation and impact.
• Competitive salary, stock options, and benefits.
• Hybrid working and flexibility.

Interview Process

1. Recruiter Call – Introduction & background
2. Technical Interview – Deep dive into ML design, feature engineering, and evaluation
3. Practical Task – Model development or analysis challenge
4. Final Interview – Team fit, leadership approach, and business alignment