National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Backend Software Engineer

CATCHES
united kingdom, united kingdom
2 months ago
Applications closed

Related Jobs

View all jobs

Python Software Engineer

Senior Data Engineer, Consultant

Oracle Data Engineer

Machine Learning Engineer

Machine Learning Engineer Language

Lead Data Engineer

Location:Fully remote with the opportunity of working in a co-working space local to you


About:

CATCHES are a SaaS start-up backed by some of the most influential names in luxury fashion globally. We've partnered with the global leaders in cloud computing and AI to integrate advanced 3D rendering, Artificial Intelligence (AI) and Visual Effects (VFX) techniques to create unparalleled shopping experiences for luxury fashion and exclusive events.


Role:

We are seeking a highly skilled Backend Software Engineer to join our team. The ideal candidate will have experience building APIs and backend services, ideally in C#.NET.

In this role, you’ll build robust, scalable, and secure backend systems powering our SaaS platform. You will collaborate closely with the frontend team, data engineers, and other stakeholders to deliver high-quality software solutions that meet our product's needs.

You’ll have input into technical direction and contribute to shaping backend architecture as we scale.


Responsibilities:

  • Design, develop, and maintain APIs and services primarily usingC#.NET.
  • Build scalable, fault-tolerant systems for a cloud-native environment (primarilyGCP).
  • Implement event-driven workflows usingRabbitMQ.
  • Collaborate with product, design, data, and frontend teams to ship end-to-end features.
  • Own your code in production, participate in code reviews, and improve system observability.
  • Champion clean code, security best practices, and scalable architecture.


Requirements:

  • 4+ years experience building backend systems, ideally in C#.NET.
  • Solid grasp ofPostgreSQLor equivalent relational databases.
  • Cloud deployment experience (GCP preferred, but AWS/Azure welcome).
  • Comfort withevent-driven architecturesandmessage queues.
  • Experience shipping production-grade systems with performance, security, and observability in mind.
  • Ability to work independently in a fast-moving, startup environment.
  • Strong communication skills and a collaborative mindset.
  • Experience delivering pragmatic solutions and implementing iterative design approaches.
  • Strong understanding of engineering fundamentals, including design patterns, SOLID principles, and clean code.


Nice to Have:

  • NoSQL Database experience.
  • Experience withKubernetesor other orchestration systems.
  • Exposure tobare metaldeployments or hybrid cloud environments.
  • DevOps practices: Infrastructure as Code, monitoring, and alerting.
  • Some experience with frontend development or WebGL/3D rendering pipelines.


What Working with Catches Looks Like:

  • Workfully remotewith optional coworking access.
  • Be part of asmall, experienced teamthat values shipping, experimentation, and autonomy.
  • Contribute early to product and architecture decisions.
  • Use cutting-edge tech to shape the future of immersive eCommerce.
  • Enjoy startup pace without burnout: async-first, high ownership, minimal meetings.


Tech Stack:

  • Languages: C#.NET (primary), Go, Python.
  • Databases: Postgres, Redis.
  • Messaging: RabbitMQ.
  • Infra: Docker, Kubernetes, GCP (primary), AWS, Azure & bare-metal.
  • CI/CD: GitHub Actions.
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.