Job Title: Senior Machine Learning Engineer - Product Intelligence

Company Name: Cloudshelf

Job Details: £85k-£105k/yrRemoteFull,Time

Job Url: https://hiring.cafe/viewjob/72ci2gwspkgbdb51

Job Description: Posted 3mo agoSenior Machine Learning Engineer - Product Intelligence@ CloudshelfView All JobsWebsiteLondon, England, United Kingdom£85k-£105k/yrRemoteFull TimeResponsibilities:Design recommendations, Build data pipelines, Measure performanceRequirements Summary:3+ years ML for product problems; strong TypeScript backend; deep SQL; experience building recommender systems; end-to-end ownership; strong communication.Technical Tools Mentioned:TypeScript, SQL, Big Data, Machine Learning
Cloudshelf | Remote (UK-compatible timezone) | Seed-stage | Equity + Competitive SalaryAbout CloudshelfCloudshelf is transforming retail experiences by bringing the full power of online shopping into physical stores. Our API-first platform integrates with major eCommerce platforms (Shopify, Salesforce Commerce Cloud, etc) to power in-store kiosks, tablets, and touchscreen displays that help retailers extend their product ranges and drive conversion.We're a small, focused team on the cusp of seed funding, building technology that's already deployed with retailers in most verticals and all over the world, making a real impact on how people shop.The RoleWe're looking for a Senior Machine Learning Engineer who can design, build, and optimize the intelligent systems that power our product recommendations, buyer guides, and upsell/cross-sell features. This isn't about building models from scratch - it's about cleverly leveraging existing ML capabilities (including LLMs) and creating the feedback loops that make them better over time.You'll work directly with our CEO (Head of Product) and report to our CTO, with a clear path to a staff-level role as we scale. This is a unique opportunity to own the intelligence layer of a platform that's changing how retail works on a global level.What You'll DoDesign & StrategyArchitect recommendation systems that identify product complementarity and drive upsell opportunities across diverse product catalogsDesign scoring algorithms and business logic for buyer guides that help customers make confident purchase decisionsDefine the metrics and feedback loops that continuously improve recommendation qualityBuild & ShipImplement production-grade features that integrate seamlessly with our API-first architectureBuild data pipelines that process product catalogs from multiple eCommerce platformsWrite clean, maintainable, tested TypeScript backend code that other engineers can work withOptimize for performance and scale as we grow our retail footprintMeasure & IterateInstrument tracking systems to understand how recommendations perform in real retail environmentsRun experiments to validate algorithm improvements and feature variationsUse SQL to analyze product data, user behavior, and conversion patternsTurn insights into actionable product improvementWhat We're Looking ForRequired:3+ years of experience applying machine learning to real-world product problemsStrong backend engineering skills, particularly in TypeScriptDeep SQL expertise - you're comfortable writing complex queries and working with large datasetsExperience building and deploying recommendation systems, ideally in eCommerce or retail contextsTrack record of owning features end-to-end: from concept through production deployment and optimizationPragmatic approach to ML - you know when to use sophisticated techniques and when simpler solutions winConfidence to push back on use of data sets we shouldn't be "learning" from Excellent communication skills - you can discuss algorithms and approaches with non-technical stakeholdersBonus points for:Experience working with product catalog data and taxonomiesUnderstanding of retail dynamics and shopping behaviourBackground in experimentation and A/B testing frameworksContributions to open source or technical writingWhy Join CloudshelfImpact: Your work directly influences purchase decisions in physical stores. You'll see shoppers and retailers using systems you built, and you'll have data showing the sales outcomes you're driving.Ownership: As one of our first specialized ML hires, you'll define how intelligence works across our platform. This isn't about implementing someone else's vision - it's about shaping the product direction.Stage: We're small enough that you'll work directly with founders and have meaningful equity, but established enough to have real customers and traction. You're joining at the perfect inflection point.Team: Work with a focused engineering team that values pragmatic solutions over resume-driven development. We ship features that matter and measure what works.Flexibility: Fully remote within UK-compatible timezones. We trust you to do great work and give you the autonomy to do it your way.The Journey AheadWe're raising our seed funding, which means you'll be part of the team that scales our platform and proves out the next generation of in-store shopping technology. The problems are interesting, the impact is measurable, and the opportunity to shape both product and team is real.If you're excited about applying ML to genuine retail challenges and want to build systems that merchants and shoppers actually use, let's talk.