Senior Machine Learning Engineer ML Infrastructure

5 days ago


London, United Kingdom ASOS Full time

As a Senior Machine Learning Engineer youll focus on designing and implementing reusable ML templates deployment patterns and MLOps tooling that support scalable reliable and secure ML solutions across the organisation.Youll collaborate closely with ML Engineers and Scientists embedded in product teams such as Forecasting Recommendations Marketing Customer and Pricing helping them accelerate delivery and improve the quality of ML systems by providing a robust and standardised ML development experience.What youll be doing:Designing and developing shared ML engineering templates tooling and infrastructure to support ML teams across ASOS.Driving standardisation and reusability of ML workflows enabling consistency across diverse product domains.Enabling teams to productionise ML models efficiently by providing best practices templates and technical support.Implementing and promoting ML Ops principles including CI/CD for ML model registries monitoring testing and feature management.Collaborating with ML teams to understand pain points and evolve the platform accordingly.Partnering with Data Engineering Platform Engineering and Security teams to ensure scalable and cost-efficient ML infrastructure.We believe being together in person helps us move faster connect more deeply and achieve more as a team. Thats why our approach to working together includes spending at least 2 days a week in the office. Its a rhythm that speeds up decision-making helps ASOSers learn from each other more quickly and builds the kind of culture where people can grow create and succeed. Qualifications : About YouProfessional experience as a Machine Learning Engineer ideally with exposure to platform or infrastructure-focused work.Solid understanding of the end-to-end ML lifecycle from experimentation through deployment and monitoring.Proficiency in Python and familiarity with ML libraries like scikit-learn XGBoost PyTorch or TensorFlow.Experience with ML Ops tools and practices such as MLflow model registries containerisation (Docker/Kubernetes) and CI/CD pipelines.Comfortable working with cloud platforms (preferably Azure) and distributed computing environments (e.g. Spark Databricks).Passionate about improving developer experience through automation standardisation and tooling.Additional Information : BeneFITS Employee discount (hello ASOS discount) ASOS Develops (personal development opportunities across the business) Employee sample sales Access to a huge range of LinkedIn learning materials 25 days paid annual leave an extra celebration day for a special moment Discretionary bonus scheme Private medical care scheme Flexible benefits allowance - which you can choose to take as extra cash or use towards other benefits Remote Work : NoEmployment Type : Full-time Key Skills Active Directory Administration,Animal,Apparel,Entry Level,Jboss,Inventory Management Experience: years Vacancy: 1



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