At a Glance
- Tasks: Build and enhance machine learning systems that empower teams to innovate.
- Company: Join a forward-thinking fintech company transforming banking for everyone.
- Benefits: Competitive salary, performance incentives, remote work, and comprehensive benefits.
- Other info: Dynamic team environment with opportunities for growth and innovation.
- Why this job: Make a real impact in the AI space while shaping the future of finance.
- Qualifications: Strong backend engineering skills with experience in ML or AI platforms.
We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products – we want to solve problems and change lives through Monzo.
London / UK Remote – £85,000–£110,000 + Incentive Awards tied to your performance + Benefits
About Machine Learning Platform Engineering at Monzo
The Machine Learning Platform team builds the systems that help teams across Monzo train, evaluate, deploy and serve ML models and AI features safely and reliably. We work on backend services, Python libraries, model lifecycle tooling, evaluation workflows and low-latency serving systems. Our users are internal ML engineers, scientists and product teams building with ML and LLMs. The work matters because machine learning powers many important decisions and experiences at Monzo, from fraud checks and credit decisions to customer operations. We help teams move faster while keeping production systems reliable, observable and safe. This is a platform engineering role in the ML and AI space. We’re looking for someone who combines strong software engineering foundations with ML or AI context, and who enjoys building tools and systems for other engineers.
What you’ll be working with:
- Go for backend services, platform APIs, and production systems
- Python for libraries, workflows, and tooling used by our ML engineers and scientists
- Feature platforms and data workflows using Chronon, Feast, and DataHub
- Model training pipelines and experiment tracking using Vertex AI and Comet
- AI observability, evaluation, and tracing using Langfuse and Bifrost
- AWS for real-time serving and online inference, GCP for batch compute and our BigQuery data warehouse
We’d love to hear from you if:
- You combine solid backend engineering with real ML or AI platform experience (ML pipelines, feature stores, model serving, experiment tracking or LLM tooling)
- You’ve designed and operated distributed systems that handle scale, concurrency and failure
- You think like a platform engineer, focused on developer experience and removing friction for internal teams
- You’re happy working across both Go and Python
- You enjoy ambiguity and want to shape a platform as it grows
- You have experience with strongly typed languages, writing and working on backend software
- You’re curious about how systems behave in production, including reliability, latency, quality, safety and operational risk
This might NOT be the right fit if:
- Your background is predominantly SRE, DevOps or infrastructure operations
Machine Learning Platform Engineer employer: EngineersOfAI
At Monzo, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to innovate and grow. As a Machine Learning Platform Engineer, you'll be at the forefront of transforming banking through cutting-edge technology, with access to competitive salaries, performance incentives, and a range of benefits. Our London-based team thrives on collaboration and creativity, ensuring that every member has the opportunity to make a meaningful impact while enjoying a flexible work environment.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Platform Engineer
✨Tap into Campus Networks
If you're still in uni, don’t forget to engage with your campus's career services and attend finance-related events. Banks often do presentations and recruitment drives on campus, so put yourself out there and make use of these opportunities to show off your passion for the field.
✨Get Certified
Consider pursuing relevant certifications like the CFA or ACCA while you’re job hunting. They not only beef up your CV but also connect you with professional bodies which can lead to networking opportunities and even job openings in banking and financial services.
✨Connect on Professional Platforms
Join finance-focused groups on platforms like LinkedIn and engage in discussions. This can really help you stand out from the crowd, allowing potential employers to see your knowledge and interest in industry trends. Plus, you might stumble upon job postings shared exclusively within the group.
✨Apply Directly and Be Proactive
Don’t shy away from reaching out directly to firms like EngineersOfAI. Use their websites and apply through them, but also consider following up with a polite email to express your enthusiasm. Being proactive can make a huge difference in getting noticed in the competitive financial services sector.
We think you need these skills to ace Machine Learning Platform Engineer
Some tips for your application 🫡
Show Off Your Numbers!:In the banking and financial services world, quantifiable achievements are key. Make sure your CV highlights your grades in relevant subjects, any financial certifications you hold, and specific projects where you've delivered measurable results. Employers love to see how your skills translate into real-world success.
Tailor Your Cover Letter to the Role:When applying for a full-time position, your cover letter should make a direct connection between your experience and the job description. Don't just state your enthusiasm for finance—dive into how your background in banking or financial analysis sets you apart. Let your passion shine through while being specific about what you can bring to EngineersOfAI.
Include Relevant Financial Software Experience:If you've worked with financial modelling tools or software like Excel, SAP, or specific analytical tools during your studies or internships, bring that up! Highlighting your proficiency can really make your application pop and show you're ready to hit the ground running in a full-time role.
Research and Reflect:Before hitting that 'apply' button on EngineersOfAI's website, do a little digging. Look up their recent projects, values, and culture. Reflecting their ethos in your application can make a huge difference and show you’re genuinely interested in being part of the team!
How to prepare for a job interview at EngineersOfAI
✨Brush Up on Financial Analysis Skills
Make sure you're well-versed in financial concepts and analytical techniques relevant to banking and financial services. Get comfortable with tools like Excel for modelling or financial forecasting, as technical questions in this area are common during interviews with EngineersOfAI.
✨Prepare for Case Studies
Expect to tackle case studies that demonstrate your problem-solving skills in real-world banking scenarios. Familiarise yourself with the types of problems you might face—think risk assessments or investment evaluations—and be ready to articulate your thought process clearly.
✨Show Your Passion for Finance
Since this is a full-time position, employers at EngineersOfAI will be keen to see your genuine interest in finance. Be prepared to discuss recent industry trends or news articles that excite you, showcasing your enthusiasm and engagement with the field.
✨Network with Industry Professionals
Before your interview, reach out to current or former EngineersOfAI employees on platforms like LinkedIn. They'll offer unique insights into the company's culture and the interview process, which can give us a delightful edge in showcasing a good fit for the team.
