This role is being recruited for by Vecta, on behalf of one of our partner companies.
Senior Machine Learning Engineer - Credit Risk & Valuation
Location: Northampton, UK (Hybrid)
Contract: Permanent, Full-Time
Salary: Competitive Base + Annual Bonus (up to 15%)
Reports To: Head of AI & Machine Learning
The Opportunity
This is a rare chance to join a high-growth UK financial services group at the cutting edge of applied machine learning in credit risk. The business has funded over £1.5 billion for 20,000+ SMEs since 2007, operating as both a lender and broker with a panel of 60+ lending partners. It’s now investing heavily in AI and ML to sharpen its credit decisioning, automate valuation workflows, and unlock new data‑driven products.
As a Senior Machine Learning Engineer, you won’t just be maintaining models - you’ll be designing the architecture from the ground up. Working alongside the Head of AI & ML, you’ll build and deploy production credit risk and asset valuation models in AWS, develop discounted cash flow engines, and explore entirely new ML and data engineering applications that directly impact lending decisions across the business.
If you want a role where your models go live, your architecture choices matter, and your work is felt across a real lending book - not buried in a research backlog - this is it.
What You’ll Do
* Design and own the end-to-end ML model architecture for credit risk scoring, probability of default, and loss-given-default estimation.
* Build reproducible, production-grade ML pipelines - from feature engineering through training, validation, and deployment on AWS (SageMaker, Lambda, Step Functions).
* Develop and deploy discounted cash flow (DCF) models for asset valuation, integrating live market data and internal performance signals.
* Collaborate with the Head of AI & ML to define the modelling roadmap and translate complex business requirements into scalable technical solutions.
* Establish model monitoring, drift detection, and retraining frameworks to ensure models remain accurate and resilient in production.
* Work with data engineering to improve data quality, build feature stores, and ensure clean, reliable inputs for all models.
* Communicate model performance, trade‑offs, and recommendations clearly to non-technical stakeholders, including senior leadership and risk committees.
* Explore and prototype new ML applications - from automated underwriting signals to portfolio optimisation - that create measurable business value.
* Champion ML engineering best practices: version control, testing, documentation, reproducibility, and peer review.
What You’ll Bring
* Proven experience deploying machine learning models into production environments - not just notebooks, but live systems.
* Advanced Python skills with strong software engineering fundamentals (clean code, testing, CI/CD).
* Hands‑on experience with AWS services (SageMaker, S3, Lambda, EC2, or equivalent cloud ML infrastructure).
* Direct experience building or working with credit risk models (PD, LGD, EAD, scorecards, or similar).
* Strong problem‑solving ability and a bias toward pragmatic, production‑ready solutions.
* Excellent communication skills - able to translate model outputs and technical concepts for business stakeholders.
Preferred
* Understanding of financial concepts such as discounted cash flows, net present value, and yield curves.
* Experience with MLOps tooling (MLflow, Airflow, dbt, or equivalent).
* Familiarity with regulatory requirements around model risk management (e.g. SR 11‑7, PRA expectations).
The Kind of Person Who Thrives Here
* You’re calm under pressure and know how to prioritise when multiple deadlines compete for your attention.
* You’re detail‑oriented without losing sight of the bigger commercial picture.
* You’re proactive and self‑starting - you don’t wait to be told what to explore next.
* You communicate clearly in writing and in person, whether it’s a technical design doc or a board‑level summary.
* You enjoy working independently but thrive as part of a collaborative, ambitious team.
Why This Role
Your models directly influence lending decisions on a book worth hundreds of millions.
Greenfield ML architecture - you’re designing the system, not patching someone else’s.
Strong base salary plus annual bonus of up to 15%, with room to grow.
Northampton HQ with flexible hybrid arrangements.
📈 High‑Growth Business
A company that’s more than doubled in recent years, with serious ambitions ahead.
Work directly with the Head of AI & ML
About the Company
This is a well‑established, privately owned UK finance group headquartered in Northampton. Founded in 2007, the business provides SMEs with access to a comprehensive range of funding options - from asset finance and hire purchase to business loans and government‑backed schemes. Operating as both a direct lender and a broker with a panel of 60+ partners, the company has arranged over £1.5 billion in funding for more than 20,000 businesses across every sector.
The business is highly rated by its customers (4.8 stars across 900+ reviews) and has more than doubled in size in recent years. It is now making a significant investment in AI and machine learning to transform its credit risk, underwriting, and valuation capabilities - and this role is central to that ambition.
Please note: as part of the recruitment process, a criminal records check and a credit history check will be carried out by an authorised third party.
#J-18808-Ljbffr