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- Tasks: Join our ML Projects team to design and implement cutting-edge machine learning features.
- Company: Starling Bank, the UK's leading digital bank with a tech-driven culture.
- Benefits: 33 days holiday, private medical insurance, and generous family-friendly policies.
- Other info: Dynamic, inclusive environment with opportunities for personal and professional growth.
- Why this job: Make a real impact in reshaping banking with innovative technology.
- Qualifications: Experience in software engineering and a passion for solving complex problems.
The predicted salary is between 50000 - 70000 £ per year.
Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way. We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.
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.
Our Data Environment
Our Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and more importantly our customers.
About the Role
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 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:
- Stage 1 - 45 mins with one of the team
- Stage 2 - Take-home challenge
- Stage 3 - 90 mins technical interview with two team members
- Stage 4 - 45 min final with two executives
Benefits
- 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
About Us
You may be put off applying for a role because you don't tick every box. Forget that! While we can’t accommodate every flexible working request, we're always open to discussion. So, if you're excited about working with us, but aren’t sure if you're 100% there yet, get in touch anyway. We’re on a mission to radically reshape banking – and that starts with our brilliant team. Whatever came before, we’re proud to bring together people of all backgrounds and experiences who love working together to solve problems. Starling Bank is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace.
Software Engineer (ML Projects) in London employer: Engine
Contact Detail:
Engine Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer (ML Projects) in London
✨Tip Number 1
Get to know Starling's values! When you’re prepping for your interview, think about how you can demonstrate that you listen, keep it simple, and aim for greatness. We love seeing candidates who align with our mission to transform banking.
✨Tip Number 2
Show off your problem-solving skills! Be ready to discuss past projects where you tackled complex challenges, especially in ML or software engineering. We want to see how you own your work and drive solutions from start to finish.
✨Tip Number 3
Don’t shy away from asking questions during the interview! It’s a two-way street, and we want to make sure you’re as excited about us as we are about you. Ask about our tech stack, team culture, or anything else that sparks your curiosity.
✨Tip Number 4
Apply through our website! It’s the best way to get your application in front of us. Plus, you’ll find all the info you need about the role and our team. Let’s change banking together!
We think you need these skills to ace Software Engineer (ML Projects) in London
Some tips for your application 🫡
Show Your Passion for Tech: When you're writing your application, let your enthusiasm for technology and innovation shine through. We love seeing candidates who are genuinely excited about building and improving systems, so share your experiences and projects that reflect this passion!
Tailor Your Application: Make sure to customise your application to fit the role of Software Engineer in ML Projects. Highlight relevant skills and experiences that align with our tech stack and values. This shows us that you’ve done your homework and are serious about joining our team.
Be Yourself: We want to get to know the real you! Don’t be afraid to inject a bit of personality into your application. Share your unique perspective and how you approach problem-solving. Remember, we value attitude and aptitude over specific qualifications.
Apply Through Our Website: For the best chance of getting noticed, make sure to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you’re considered for the role. Plus, it shows you’re keen to join the Starling family!
How to prepare for a job interview at Engine
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, Java, and cloud services like AWS and GCP. Be ready to discuss your experience with these tools and how you've used them in past projects.
✨Show Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in software engineering, particularly in machine learning projects. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your ability to find elegant solutions.
✨Ask Thoughtful Questions
Interviews are a two-way street! Prepare insightful questions about Starling's culture, the ML Projects team, or their approach to innovation. This shows your genuine interest and helps you assess if the company is the right fit for you.
✨Embrace the Open Culture
Starling values collaboration and support. During your interview, express your enthusiasm for teamwork and how you’ve contributed to a positive team environment in the past. Highlight your willingness to share knowledge and learn from others.