Senior Machine Learning Engineer

About Lendable

Lendable is on a mission to make consumer finance amazing: faster, cheaper, and friendlier. We're building one of the world’s leading fintech companies and are off to a strong start:

• One of the UK’s newest unicorns with a team of just over 500 people

• Among the fastest-growing tech companies in the UK

• Profitable since 2017

• Backed by top investors including Balderton Capital and Goldman Sachs

• Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)

So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days.

We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.

Join us if you want to

1. Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1

2. Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo

3. Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting

About the role

We’re looking for an experienced machine learning engineer to join us as the newest member of the Data Science Infrastructure team. The team is responsible for designing, developing, and maintaining the critical high-performance services that support our underwriting capabilities across the entire business. In addition we work closely with both the rest of the data science team and credit analysts to create tools to enhance productivity. This role will be key to us delivering as we expand further in both the UK and the US.

Our Tech Stack

• Python

• Pytorch

• FastAPI

• AWS

• Docker

• Kubernetes

• ArgoCD

What you’ll be doing/impact on objectives

• Develop key services that power our underwriting capabilities

• Deploy, optimise, update and maintain our underwriting models & services across all our products and regions

• Create libraries that enables our data science team to more efficiently create the next generation of models

What we’re looking for

• Detailed knowledge of managing services in Kubernetes

• Solid experience with Python web application frameworks like FastAPI

• Strong engineering principles - design patterns, unit testing, code reviews

• A keen desire to both learn from and upskill other team members

Nice to have

• Experience deploying models using GPU in production environments

• Experience working with physical servers

Interview process

• A quick phone call with one of the team

• A short coding exercise to complete in your own time

• Video Interview for 60-90mins

  • Discuss the exercise you completed

  • Technical interview questions

  • Meet the team you’ll work with daily

• 2x Onsite interviews for 30mins each

  • Behavioural/culture interview

  • Any questions you have about the company, role, etc

Check out our blog

We also have an engineering blog where we have written in more detail about how we work in the engineering team.

Life at Lendable

• The opportunity to scale up one of the world’s most successful fintech companies.

• Best-in-class compensation, including equity.

• You can work from home every Monday and Friday if you wish - on the other days, those based in the UK come together IRL at our Shoreditch office in London to be together, build and exchange ideas.

• Enjoy a fully stocked kitchen with everything you need to whip up breakfast, lunch, snacks, and drinks in the office every Tuesday-Thursday.

• We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes to private health insurance

• We're an equal-opportunity employer and are looking to make Lendable the most inclusive and open workspace in London

Check out our blog!