ML​/AI Platform Engineer

Overview

We have around 600 engineers out of roughly 5,000 people in total - and we have big ambitions. There are many interesting challenges ahead, and we’re happy for people to move between teams or to specialise, whatever you prefer. As an engineer here you’d be able to work directly with anyone across the company, and we run regular knowledge-sharing sessions so you’ll learn heaps about everything from how banks work to effective communication.

• The Machine Learning Platform team builds the systems that help teams across Monzo train, evaluate, deploy and serve machine learning 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 use a mix of backend, ML and infrastructure technologies. Please note direct experience with all of them is helpful but not required and our interview process can be completed in any language
• Go for backend services, platform APIs and production systems
• Python for libraries, workflows and tooling used by ML engineers and scientists
• ML and AI platform systems such as model serving, evaluation, feature engineering, experiment workflows and LLM infrastructure
• Kubernetes, AWS, GCP, Terraform and Envoy Proxy to run reliable systems in production

• Contribute to and own tooling and systems for training, evaluating, deploying and serving ML models and AI features
• Build backend services, libraries and workflows used by ML engineers, scientists and product teams
• Design and operate distributed systems that handle scale, concurrency and failure
• Collaborate with internal teams to improve developer experience and remove friction for internal users

• You’ve worked with AWS or GCP, and with Kubernetes
• You have experience with strongly typed languages, writing and working on backend software
• You’ve designed and operated distributed systems that handle scale, concurrency and failure
• You’re curious about how systems behave in production, including reliability, latency, quality, safety and operational risk
• You think like a platform engineer, focused on developer experience and removing friction for internal teams
• You combine solid backend engineering with real ML or AI platform experience (ML pipelines, feature stores, model serving, experiment tracking or LLM tooling)
• You’re happy working across both Go and Python
• You enjoy ambiguity and want to shape a platform as it grows

• Yearly Salary Review + Proactive pay increases to reflect growing responsibilities + Share options
• Flexible working hours
• Work From Home Opportunities + we’ll pay for any equipment you need to do your job
• 24 days holiday a year, plus bank holidays
• Employee Assistance Programme
• Paid sick leave for both physical & mental health + Health insurance via AXA or Vitality + Additional health insurance through Medicash
• Learning budget of £1,000 a year
• Aviva Pension Scheme + 4% Employer Contribution
• Paid maternity, paternity, adoption or shared parental leave (after 13 weeks of employment)
• 52 weeks of primary caregiver leave (6 months at 100% pay, 13 weeks at Statutory Maternity Pay, 13 weeks unpaid)
• 3 months of secondary caregiver leave at 100% pay
• Unum Life Insurance
• Access to fertility and family-forming health benefits via Fertifa
• Abellio Season Travel Tickets + Cycle-to-Work Scheme