Описание:
ASOS is a fashion and technology company whose platform is used by millions. Machine learning supports how customers discover products, engage with the brand and shop.
Задачи:
- Design, build and operate machine learning systems for customer engagement, marketing effectiveness, pricing and commercial decision-making
- Own the end-to-end engineering lifecycle of machine learning products, including data ingestion, feature engineering, deployment, monitoring and optimisation
- Productionise advanced machine learning solutions and ensure they operate reliably at ASOS scale
- Partner with Applied Scientists to turn research and experimentation into scalable production systems
- Contribute to engineering best practices, operational excellence and capabilities for the MLOps platform
- Build reusable tooling, frameworks and infrastructure to accelerate machine learning delivery and reduce operational overhead
- Influence technical direction and architectural decisions across machine learning products and platforms
- Mentor colleagues and support high standards of engineering quality, reliability and scalability
Требования:
- Experience building, deploying and operating machine learning systems in production environments
- Strong software engineering fundamentals, including expertise in Python and modern engineering practices
- Experience building scalable batch and real-time machine learning pipelines in cloud environments
- Strong understanding of MLOps principles, including model deployment, monitoring, CI/CD, 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 technologies
- Experience designing reliable APIs, services and platforms that support machine-learning-powered products
- Ability to work through ambiguity and lead complex technical initiatives
- 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 beyond the immediate team
- Track record of delivering machine learning solutions with measurable customer or commercial outcomes
Условия:
- Employee discount and employee sample sales
- 25 Days of paid annual leave plus an extra celebration day
- Discretionary bonus scheme
- Private medical care scheme
- Flexible benefits allowance, available as extra cash or for other benefits
- Personalised learning and in-the-moment experiences
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