Machine learning engineer in MLOps

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. 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.

• 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.

• 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.
• Comfortable providing technical leadership, mentoring engineers and influencing architectural direction.
• Strong collaboration and communication skills, with experience working in cross-functional product teams.
• Будет плюсом: 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; 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

• Employee discount (hello ASOS discount!)
• Employee sample sales
• 25 days paid annual leave + an extra celebration day for a special moment
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
• Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role