Overview
Asos seeks a Senior ML Engineer to design, deploy and scale ML products that drive customer growth, marketing effectiveness, pricing and personalisation. You will operate across the full ML lifecycle, from ideation and experimentation to deployment, monitoring and optimisation, collaborating with scientists and data engineers. You’ll work with rich datasets to build production-grade systems that deliver measurable value for customers and the business at scale. This role offers impact on customer experiences and commercial outcomes, with opportunities to shape the ML platform and engineering standards. You will be part of a cross-functional team shaping the future of ASOS’s ML capabilities.
Pay / Benefits
- employee discount
- employee sample sales
- 25 days paid annual leave + extra day
- discretionary bonus scheme
- private medical care
- flexible benefits allowance
Responsibilities
- Design, build and operate ML systems supporting engagement, marketing effectiveness, pricing and commercial decision-making
- Own end-to-end ML product lifecycle: data ingestion, feature engineering, deployment, monitoring and optimisation
- Productionise ML solutions to run reliably at ASOS scale
- Collaborate with Applied Scientists to translate research into scalable production systems
- Contribute to MLOps platform by enhancing engineering practices and platform capabilities
- Build reusable tooling, frameworks and infrastructure to accelerate ML delivery
- Influence technical direction and architectural decisions across ML products
- Mentor engineers and uphold high standards of quality, reliability and scalability
Key requirements
- Experience building, deploying and operating ML systems in production
- Strong Python software engineering fundamentals 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 technologies such as Spark
- Proficiency with ML frameworks such as 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 own team
- Proven track record delivering ML solutions with measurable outcomes
- ambition and impact-minded
- collaborative and cross-functional
- ability to work through ambiguity
- Python
- Spark
- PyTorch
…