software engineer
Role details
Job location
Tech stack
Job description
The ML Projects team is at the forefront of bringing cutting edge machine learning to the core of what we do at Starling. As a software engineer on the ML Projects team you will work with other engineers and data scientists to design, implement and maintain features that make use of machine learning models under the hood. This could mean anything from creating a brand new ML-powered feature from scratch to seamlessly integrating a new model into our core banking platform. You might find yourself designing robust infrastructure and pipelines or discovering a completely new approach to a complex problem.
We believe in empowering our engineers to take ownership and drive solutions from ideation to launch. This means you'll have the autonomy to shape your own path, identify challenges, and collaborate with colleagues across teams to deliver impactful solutions across a range of technologies.
Requirements
We are looking for a skilled software engineer who thrives on building and scaling complex systems. You should have a proven track record of delivering robust, multi-technology applications within an enterprise environment.
We're open-minded when it comes to hiring and we care more about aptitude and attitude than specific qualifications. We are very open about how we deliver software. We believe in clean coding, simple solutions, automated testing and continuous deployment. If you care enough to find elegant solutions to difficult technical problems, we'd love to hear from you.
The main part of our Tech Stack is listed below, we don't ask that you have experience in all of this, but if you do, that's great!
- Python
- Java, which makes up the majority of our backend codebase
- JavaScript, particularly React, which makes up our frontend
- Postgres and SQL
- AWS & GCP - we're cloud-native
- TeamCity for CI / CD (lots of teams are releasing code 15-20 times per day!)
- Terraform
- Prometheus and Grafana
If you have built and deployed complex Python applications or have hands-on experience with generative AI and LLMs, we would be especially keen to talk. We are moving fast in the AI space and want people who are excited to help us define what comes next.
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
Benefits & conditions
- 33 days holiday (including public holidays, which you can take when it works best for you)
- An extra day's holiday for your birthday
- Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off
- 16 hours paid volunteering time a year
- Salary sacrifice, company enhanced pension scheme
- Life insurance at 4x your salary & group income protection
- Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
- Generous family-friendly policies
- Incentives refer a friend scheme
- Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
- Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing