4 hours ago
London, United KingdomSenior
Responsibilities
- Design, build, and operate machine learning systems for customer engagement, marketing effectiveness, pricing, and commercial decision-making.
- Own the full engineering lifecycle of ML products, including data ingestion, feature engineering, deployment, monitoring, and optimisation.
- Productionise advanced machine learning solutions and ensure reliable operation at ASOS scale.
- Partner with Applied Scientists to translate research and experimentation into scalable production systems.
- Build reusable tooling, frameworks, feature platforms, and infrastructure that accelerate ML delivery.
- Contribute to MLOps platform capabilities, engineering standards, operational excellence, and architectural decisions.
- Mentor colleagues and influence technical direction beyond the immediate team.
Requirements
- Experience building, deploying, and operating machine learning systems in production.
- Strong software engineering fundamentals and expertise in Python.
- Experience building scalable batch and real-time machine learning pipelines in cloud environments.
- Strong understanding of MLOps principles, model deployment, monitoring, observability, and operational excellence.
- Experience with large-scale data processing technologies such as Spark.
- Strong understanding of machine learning frameworks such as PyTorch, TensorFlow, XGBoost, or similar.
- Experience designing reliable APIs, services, and platforms supporting machine-learning-powered products.
- Ability to lead complex technical initiatives through ambiguity.
- Experience in customer intelligence, marketing optimisation, pricing, forecasting, or personalisation.
- Experience building feature platforms, ML platforms, or shared machine learning infrastructure.
- Exposure to experimentation frameworks, causal inference, or measurement platforms.
- Experience mentoring engineers and influencing technical direction.
- Track record of delivering machine learning solutions with measurable customer or commercial outcomes.
Benefits
- Employee discount and access to employee sample sales.
- 25 days of paid annual leave plus an additional celebration day.
- Discretionary bonus scheme.
- Private medical care scheme.
- Flexible benefits allowance that can be taken as cash or used toward other benefits.
- Personalised learning opportunities and in-the-moment development experiences.
Tech Stack
Categories
About ASOS
ASOS is a global online fashion and beauty retailer for 20‑somethings, selling own‑brand and third‑party labels via its website and mobile apps. The company earns revenue from direct‑to‑consumer e‑commerce, shipping to customers worldwide and offering marketplace services for brands. Founded in 2000 and headquartered in London, ASOS is a public company listed on the London Stock Exchange and runs in‑house content and fulfillment operations at scale.