Machine learning engineer in MLOps

ASOS.com; Greater London; Presencial; GBP 110.000 - 140.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Employee discount

Sample sales

25 days leave

Discretionary bonus

Private medical care

Flexible benefits

Learning opportunities

Descripción de la vacante

ASOS.com is seeking a Senior Machine Learning Engineer with strong engineering experience to design, build and operate scalable ML platforms and production infrastructure. You will enable models to be trained, deployed and served reliably at scale.

You will lead backend services powering recommendations, search and personalization, build CI/CD for ML/data products, and mentor engineers while shaping ASOS's ML platform strategy.

Formación

• Strong software engineering fundamentals with production-scale systems experience.
• Experience with distributed systems, microservices, or high-throughput backends.
• Proficient in Python, Java, Kotlin, Go, Scala or similar.
• Experience deploying on AWS/Azure/GCP.
• Hands-on Kubernetes, containerisation and cloud-native tech.
• CI/CD pipelines and automated deployment expertise.
• Infrastructure-as-Code tools: Terraform, Pulumi, CloudFormation.
• Monitoring, alerting and observability tooling.
• Experience building reliable, scalable systems with performance focus.
• Experience with data-intensive or large-scale distributed processing.
• Strong technical leadership, mentoring and architecture direction.
• Excellent collaboration in cross-functional teams.

Responsabilidades

• Design and build scalable ML platforms and infrastructure for training, deployment and serving.
• Develop backend services powering recommendations, search and personalization at scale.
• Build and maintain CI/CD pipelines for ML and data products.
• Design batch and real-time inference architectures using cloud-native technologies.
• Improve reliability, resilience and performance across ML workloads with monitoring and automation.
• Build tooling and frameworks enabling data scientists to deploy models safely.
• Own production services, infrastructure and incident management practices.
• Optimise distributed compute workloads and resource utilisation across cloud environments.
• Drive IaC adoption and platform standardisation across ML systems.
• Contribute to architectural decisions across recommendation, search and AI platforms.
• Mentor engineers and promote software engineering best practices across the organisation.

Conocimientos

Software engineering fundamentals

Distributed systems / microservices

Programming languages

Cloud platforms

Kubernetes / containerisation

CI/CD pipelines

Infrastructure-as-Code

Monitoring & observability

Data-intensive / distributed systems

Leadership & mentoring

Herramientas

Kubernetes

Terraform

Pulumi

CloudFormation

CI/CD tooling

Descripción del empleo

Описание

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.

Задачи

• 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.

Требования

• 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

Условия

• 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