Senior Machine Learning Engineer (MLOps)

As Senior Machine Learning Engineer in ASOS’s Search & Recommendations team, you design, build and operate scalable ML platforms that train, deploy and serve models for product discovery at scale. You’ll work with scientists, engineers and PMs to deliver reliable, cloud-native infrastructure for search, recommendations and personalization. The role focuses on automation, observability and platform excellence across production ML workloads. You help shape the long-term ML platform strategy and mentor others.

• Employee discount
• Employee sample sales
• 25 days paid annual leave + extra day
• Discretionary bonus scheme
• Private medical care
• Flexible benefits allowance

• Design and build scalable ML platforms for training, deployment and serving
• Develop highly available backend services powering recommendations, search and personalization
• Build and maintain CI/CD pipelines for ML and data products
• Design batch and real-time inference architectures using cloud-native tech
• Improve reliability, resilience and performance via monitoring and automation
• Create tooling to enable safe, efficient model deployment by data scientists and ML engineers
• Own production services and operational excellence practices, including incident management and RCA
• Optimize distributed compute and resource usage across clouds
• 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
• Help shape ASOS’s long-term ML platform strategy

• Experience designing and building production systems at scale
• Experience with distributed systems, microservices or high-throughput backends
• Programming skills in Python, Java, Kotlin, Go, Scala or similar
• Experience with AWS, Azure or GCP
• Hands-on with Kubernetes and cloud-native technologies
• Experience implementing CI/CD pipelines
• Knowledge of IaC tools like Terraform, Pulumi or CloudFormation
• Experience with monitoring, alerting and observability tooling
• Experience building reliable and scalable systems with performance focus
• Experience with data-intensive or large-scale distributed processing
• Exposure to ML systems, model serving, feature stores, MLOps
• Experience supporting recommendation or search/personalization systems
• Technical leadership, mentoring and architectural influence
• Strong collaboration and cross-functional communication skills
• Experience with large-scale model training and inference workloads
• Knowledge of vector search, ranking, retrieval architectures or recommendation platforms
• Exposure to LLMs, Generative AI and production AI systems
• Experience building internal developer platforms or enablement tooling

• collaboration
• mentoring
• communication
• Python/Java/Kotlin/Go/Scala
• AWS/Azure/GCP
• Kubernetes