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.
