Senior Machine Learning Engineer

Overview

As a Senior Machine Learning Engineer in ASOS’s Customer & Martech team, you will design, deploy and scale ML solutions that drive customer growth, marketing effectiveness, pricing and personalisation. You’ll own end-to-end ML product lifecycles and partner with scientists and data engineers to translate research into production systems. You’ll help shape our MLOps platform and build reusable tooling to accelerate delivery at scale. This role offers impact across customer experience and commercial outcomes.

Pay / Benefits

• employee discount
• employee sample sales
• 25 days paid annual leave
• discretionary bonus scheme
• private medical care
• flexible benefits allowance

Responsibilities

• Design, build and operate ML systems for engagement, marketing effectiveness, pricing and commercial decisions
• Own end-to-end ML product lifecycle: data ingestion, feature engineering, deployment, monitoring and optimisation
• Productionise ML solutions ensuring reliability at ASOS scale
• Collaborate with Applied Scientists to translate research into scalable production
• Contribute to MLOps platform, engineering best practices and platform capabilities
• Build reusable tooling, frameworks and infrastructure to accelerate ML delivery
• Influence technical direction and architectural decisions across ML products/ platforms
• Mentor engineers and uphold high standards of reliability and scalability

Key requirements

• Experience building, deploying and operating ML systems in production environments
• Strong software engineering fundamentals with Python and modern practices
• Experience building scalable batch and real-time ML pipelines in cloud environments
• Solid understanding of MLOps: deployment, monitoring, CI/CD, observability
• Experience with large-scale data processing (Spark)
• Knowledge of ML frameworks (PyTorch, TensorFlow, XGBoost)
• Designing reliable APIs/services for ML-powered products
• Ability to navigate ambiguity and lead complex technical initiatives
• Experience in customer intelligence, marketing optimisation, pricing, forecasting or personalisation
• Experience building feature platforms or shared ML infrastructure
• Exposure to experimentation frameworks, causal inference or measurement platforms
• Mentoring engineers and influencing technical direction beyond immediate team
• Track record of delivering ML solutions with measurable customer or commercial outcomes

• Collaborative mindset
• Technical leadership
• Adaptability and problem-solving
• Python
• Cloud computing
• Spark

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