4 days ago
London, United KingdomStaff+
Responsibilities
- Own end-to-end technical architecture for personalized fashion discovery, recommendations, ranking, retrieval, search relevance, and AI Stylist systems.
- Lead the design and evolution of large-scale batch and real-time machine learning systems serving millions of customers.
- Translate machine learning research and experimentation into scalable, reliable, production-grade customer-facing systems.
- Set technical direction and engineering standards across recommendation, personalization, deep learning, generative AI, and ML platform initiatives.
- Drive cross-team architecture, platform investment, build-versus-buy, scalability, reliability, and performance decisions.
- Develop shared machine learning capabilities, tools, and frameworks for Search & Discovery and wider engineering teams.
- Mentor Senior and Staff engineers and promote engineering excellence and responsible use of AI-assisted development tools.
- Influence multiple teams and communicate technical strategy, trade-offs, and outcomes to technical and non-technical stakeholders.
Requirements
- Extensive experience designing, building, and operating large-scale machine learning systems in production.
- Experience owning and influencing technical architecture across complex engineering ecosystems.
- Extensive experience across data analysis, feature engineering, model development, evaluation, deployment, monitoring, and continual ML improvement.
- Experience building scalable, observable, and highly reliable ML services using cloud technologies, distributed infrastructure, and large datasets.
- Deep expertise in at least two areas such as ranking and relevance, recommendation systems, deep learning, large language models, information retrieval, natural language processing, or content understanding.
- Advanced hands-on experience with PyTorch, TensorFlow, or similar machine learning frameworks.
- Strong programming skills in Python and/or languages such as Java or C++.
- Deep understanding of MLOps, deployment, observability, monitoring, and lifecycle management at scale.
- Experience building production AI systems using retrieval-augmented generation, agent-based architectures, retrieval systems, model evaluation frameworks, and ML-driven scoring.
- Significant experience using AI-assisted engineering tools and coding agents such as Claude Code, Codex, or Cursor.
- Demonstrated ability to establish technical vision, influence multiple teams without direct management responsibility, set architectural direction, and drive adoption of standards.
- Experience mentoring senior engineers and engaging with senior technical and business leaders.
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.
- Personalized learning and in-the-moment development experiences.
- The posting does not state a work arrangement or location policy.
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.