> Markdown version of [/jobs/ext/3134470-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3134470-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** asos.com Ltd - **Location:** UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Engineering, Computer Programming, Continuous Delivery, Distributed Systems, Python (Programming Language), Machine Learning, Recommender Systems, Reliability Engineering, Scala (Programming Language), Search Technologies, Software Construction, Software Engineering, Datadog, Pulumi, Large Language Models, Generative AI, Backend, Cloudformation, Kotlin, Build Management, Containerization, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Deployment Automation, Machine Learning Operations, Video Streaming, Terraform, Golang, Microservices - **Published:** September 29, 2026 - **Apply:** https://startup.jobs/senior-machine-learning-engineer-mlops-asos-10213115 ## About the Role We're looking for a Senior Machine Learning Engineer - with strong Engineering experience - who enjoys solving complex engineering challenges at scale. This role is ideal for someone with a strong software engineering/MLOps, distributed systems or platform engineering background who wants to work at the intersection of machine learning and production infrastructure., * Strong software engineering fundamentals with experience designing and building production systems at scale. * Experience developing distributed systems, microservices or high-throughput backend platforms. * Strong programming skills in Python, Java, Kotlin, Go, Scala or similar languages. * Experience building and operating services in AWS, Azure or GCP environments. * Hands-on experience with Kubernetes, containerisation and cloud-native technologies. * Experience implementing CI/CD pipelines and automated deployment processes. * Knowledge of Infrastructure-as-Code tools such as Terraform, Pulumi or CloudFormation. * Experience with monitoring, alerting and observability tooling. * Experience building reliable, resilient and scalable systems with a focus on performance and operational excellence. * Experience working with data-intensive systems, streaming technologies or large-scale distributed processing platforms. * Exposure to machine learning systems, model serving, feature stores, training infrastructure or MLOps practices. * Experience supporting recommendation systems, search platforms, personalisation engines or other customer-facing data products is advantageous. * Comfortable providing technical leadership, mentoring engineers and influencing architectural direction. * Strong collaboration and communication skills, with experience working in cross-functional product teams. * Experience supporting large-scale model training and inference workloads. * Knowledge of vector search, ranking systems, retrieval architectures or recommendation platforms. * Exposure to LLMs, Generative AI and production AI systems. * Experience building internal developer platforms, engineering enablement tooling or shared capabilities used across multiple teams. ## Description As a Senior Engineer, you'll be responsible for designing, building and operating the platforms and services that enable machine learning models to be trained, deployed and served reliably across ASOS. You'll work closely with Applied Scientists, Software Engineers, Data Engineers and Product Managers to create the tooling, infrastructure and deployment frameworks that power recommendation systems, search relevance, personalisation and emerging AI applications. This is a highly engineering-focused role with an emphasis on cloud-native systems, platform architecture, automation, observability and operational excellence. What You'll Be Doing: * Design and build scalable machine learning platforms and infrastructure supporting model training, deployment and serving. * Develop highly available backend services that power recommendation, search and personalisation experiences for millions of customers. * Build and maintain CI/CD pipelines for machine learning and data products. * Design batch and real-time inference architectures using modern cloud-native technologies. * Improve reliability, resilience and performance across ML workloads through monitoring, observability and automation. * Build tooling and frameworks that enable data scientists and ML engineers to deploy models safely and efficiently. * Own production services, infrastructure and operational excellence practices, including incident management and root cause analysis. * Optimise distributed compute workloads and resource utilisation across cloud environments. * Drive Infrastructure-as-Code adoption and platform standardisation across machine learning systems. * Contribute to architectural decisions across recommendation, search and AI platforms. * Mentor engineers and promote software engineering best practices across the organisation. * Help shape ASOS's long-term machine learning platform strategy. We're interested in candidates who bring experience across modern software engineering, distributed systems and machine learning infrastructure. We recognise that expertise can be developed through a variety of backgrounds, including Backend Engineering, Platform Engineering, Site Reliability Engineering (SRE), Cloud Engineering, MLOps or Machine Learning Engineering. ## Related Videos - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Why segmenting your infrastructure into tiers makes your infrastructure design better](https://www.wearedevelopers.com/videos/1960-why-segmenting-your-infrastructure-into-tiers-makes-your-infrastructure-design-better) - [Kotlin Multiplatform - True power of native code reuse](https://www.wearedevelopers.com/videos/4-kotlin-multiplatform-true-power-of-native-code-reuse) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Unleashing Potential Across Teams: The Power of Infrastructure as Code](https://www.wearedevelopers.com/videos/930-unleashing-potential-across-teams-the-power-of-infrastructure-as-code) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)