Machine Learning Engineer
Starling Bank, United Kingdom
Job Description
Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.
We are about giving customers a new way to spend, save and manage their money while taking better care of the planet which has seen us become a multi-award winning bank that now employs over 2800 across five offices in London, Cardiff, Dublin, Southampton, and Manchester. Our journey started in 2014, and since then we have surpassed 3.5 million accounts (and four account types!) with 350,000 business customers. We are a fully licensed UK bank but at the heart, we are a tech first company, enabling our platform to deliver brilliant products.
Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!
The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.
Hybrid Working
We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.
Our Engineering Environment
Starling engineers are excited about helping us deliver new features, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.
We are looking for engineers at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.
We want to make more and better use of machine learning at Starling - to assist with decision making, help keep our customers safe and to power features that delight our users. We are looking for people who are excited to build tooling to support the machine learning lifecycle, including especially latency-sensitive feature engineering and inference.
Responsibilities:
- Develop systems to support low latency feature engineering
- Assist with building and productionising model training pipelines
- Instrument Starling’s ML estate to be able to proactively identify unexpected behaviour changes
- Promote sound ML model lifecycle management practices
Requirements
- Proven experience in developing, deploying, and monitoring machine learning models.
- Experience with Spark or pyspark, and especially with Spark Structured Streaming
- Strong software development skills in Python or Java
- Experience with machine learning orchestration frameworks such as kubeflow
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP)
Desirables:
- Experience deploying ML models in a finance/fintech environment
- Experience with deep learning frameworks as Tensorflow or PyTorch
- Experience managing infrastructure through an infrastructure-as-code framework like Terraform
Interview process
Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:
- Stage 1 - 30 mins with one of the team
- Stage 2 - Take home challenge
- Stage 3 - 90 mins technical interview with two team members
- Stage 3 - 45 min final with an executive and a member of the people team
Benefits
- 25 days holiday (plus take your public holiday allowance whenever works best for you)<