Machine Learning Engineer – £70k-£90k – Hybrid (1-2 days/month in London)
Some companies build AI for the sake of it.
This one builds AI that changes lives.
They’ve created a lending engine that helps people access fair, affordable credit—people who would otherwise be forced into exploitative loans.
They’re growing and need a Machine Learning Engineer to take ownership of their credit risk and underwriting models.
This is a hands-on role where you’ll refine and improve a well-established risk engine, bringing in new data sources, running experiments, and optimising models that make a real difference.
You won’t just be a cog in a machine. You’ll own and shape this company’s machine learning capability.
Why this role?
🚀 Own the Machine Learning function – Be the go-to person for ML and drive the future of risk modeling.
💡 Impact-driven work – Build AI that helps people access fair credit.
🔎 Data curiosity is key – If you love experimenting, improving models, and exploring new approaches, you’ll thrive here.
🏆 Autonomy and ownership—This is a startup. There will be no hand-holding or bureaucracy. It will be just you, your expertise, and the freedom to make an impact.
Perks & Benefits
💰 Stock options – Minimum of £20k worth of shares, vesting over time.
🕒 Flexible, remote-first – Work from anywhere, with occasional in-person team meetups in London.
👩🎓 Work with a PhD ML mentor—The outgoing ML Engineer will stay part-time to guide and support you.
📈 Career growth – As the company scales, you’ll have the opportunity to expand the data science team.
What you’ll be doing
🔹 Owning and improving the company’s credit risk & underwriting ML models.
🔹 Experimenting with new data sources, refining existing models, and implementing ML best practices.
🔹 Working hands-on with BigQuery and Google Cloud to build scalable solutions.
🔹 Collaborating with a small but highly motivated team of data analysts and executives.
🔹 Being the company’s ML authority—you’ll have the space to drive AI initiatives without red tape.
Who you’ll be working with
🔹 A lean, fast-moving team – No layers of management. You’ll report directly to the CEO or CFO.
🔹 A PhD mentor – The current ML Engineer is staying on part-time to ensure a smooth transition.
🔹 A wider data team – Three data analysts focused on insights and business intelligence.
Who should apply?
✅ ML Engineers or Data Scientists with at least 2 years of experience in machine learning.
✅ Financial services experience is preferred, especially with exposure to credit risk.
✅ Comfortable working autonomously—this isn’t a structured corporate role.
✅ BigQuery and Google Cloud experience is a strong plus but not a hard requirement. Willingness to upskill in this area is important.
✅ Someone who thrives in a startup environment—you’ll be building, experimenting, and iterating quickly.
What’s next?
📩 Apply now or book a call: https://calendly.com/tomhainton/discuss-machine-learning-engineer-vacancy