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What You’ll Be Doing Behavioural Data Modelling Build and extend core behavioural models in Databricks that describe how customers interact with ASOS across web and app Design and maintain: Session logic Funnels and journeys Attribution logic Feature usage and engagement metrics Experiment exposure and variant datasets Create domain specific behavioural marts optimised for analytics and experimentation use cases Web Analytics Data Pipeline Ownership Own the quality and consistency of behavioural events flowing into Analytics platforms Ensure events conform to agreed: Schemas and naming conventions Data types and required fields Privacy first compliance Build and maintain transformation pipelines where enrichment or standardisation is required Act as a technical owner of event contracts between frontend teams and analytics Data Quality & Observability In collaboration with the teams software engineers implement end-to-end data quality checks across frontend → ingestion → Analytics → Databricks Monitor and alert on: Schema changes and validation failures Event completeness and coverage Cardinality drift Volume anomalies Identity and user stitching integrity Proactively identify and resolve issues before they impact experiments or reporting Semantic Layer Enablement Enable trusted behavioural metrics through: Databricks metric enabled views Power BI semantic models Ensure metrics are usable for: Self serve analysis Executive and leadership reporting “Talk to Data” and agent based workflows Partner with product analysts, data and product teams to ensure metrics are clear, consistent, and reusable Frontend Instrumentation Alignment Work closely with web and app engineers to ensure instrumentation meets analytics and experimentation needs Support: Event payload and schema design Instrumentation PR reviews Pre‑release validation Experiment tagging and exposure tracking Act as a go to expert for behavioural tracking best practices We’re Looking For Core Skills & Experience Experience in analytics engineering, data engineering, or product analytics Strong SQL and experience working in Databricks / Spark / DBT/ Python Solid understanding of behavioural and event based data modelling Hands‑on experience with product analytics platforms (e.g. Mixpanel, Adobe or similar) Experience building reliable data pipelines and quality controls Comfortable working closely with software engineers within product teams on data instrumentation A pragmatic, detail oriented approach to data quality Nice to Have Experience supporting experimentation and A/B testing Knowledge of identity resolution and cross device tracking Power BI semantic modelling experience Experience enabling self serve analytics Interest in AI assisted analytics or metric driven agents Employee discount (hello ASOS discount!) Employee sample sales 25 days paid annual leave + an extra celebration day for a special moment Private medical care scheme Fixed Annual Payment in addition to your salary each year, it's just an extra thank you from us Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role

We're looking for a Senior Applied Scientist to join the team – whose mission is to build machine learning capabilities that power critical business decisions, products and customer experiences across ASOS. You'll work on complex, high-impact machine learning challenges, developing scalable solutions that can be applied across a range of business domains. As we continue to expand our AI capabilities, you'll play a key role in shaping scientific approaches, identifying new opportunities for machine learning, and translating research into practical solutions that deliver measurable value. As a Senior Applied Scientist, you'll provide technical leadership across initiatives, partnering closely with ML Engineers, Data Engineers, Analysts, Product Managers and business stakeholders to design, develop and deploy machine learning solutions at scale. You'll help shape both our scientific direction and the machine learning capabilities that underpin our products and decision-making. Responsibilities Lead the design, development and evaluation of machine learning solutions for complex business challenges. Identify opportunities where machine learning can create measurable value. Drive improvements in model performance, scalability, reliability and operational impact across a range of use cases. Research, evaluate and prototype emerging approaches from industry and academia, identifying opportunities to enhance existing capabilities. Design robust evaluation frameworks to assess model quality, customer outcomes and business impact. Write, test and maintain production-quality code, applying software engineering best practices to support scalable and maintainable solutions. Partner closely with ML Engineers and Data Engineers to ensure solutions can be deployed and operated effectively at scale. Provide technical leadership on complex initiatives, influencing scientific direction and technical decision-making. Mentor and support other scientists through coaching, code reviews, knowledge sharing and technical guidance. Communicate complex technical concepts and recommendations clearly to both technical and non-technical stakeholders. You'll likely bring experience in some of the following areas: Developing and deploying machine learning solutions in production environments. Applying machine learning techniques to solve complex real-world problems. Leading the design and evaluation of data-driven solutions that deliver measurable business value. Developing new approaches or adapting research and emerging technologies to practical business challenges. Working across the end-to-end machine learning lifecycle, from problem definition and experimentation through to deployment and monitoring. Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow or similar technologies. Experience working with large datasets and distributed data processing environments. Applying software engineering best practices including testing, version control and developing maintainable, reproducible code. Collaborating effectively with engineers, product teams and business stakeholders to deliver production-ready solutions. Communicating complex technical concepts clearly to technical and non-technical audiences. Providing technical leadership, mentoring others and influencing scientific direction across projects. Curiosity, pragmatism and sound judgement when balancing innovation with business outcomes. BeneFITS’ Employee discount (hello ASOS discount!) Employee sample sales 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 Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role

We're looking for a Senior Machine Learning Engineer to join our Search and Recommendations team, where we're building the next generation of AI-powered fashion experiences at ASOS. Our mission is to help millions of customers discover complete outfits that reflect their personal style, preferences and the latest fashion trends. Sitting within ASOS's Search & Discovery organisation, the team combines recommendation systems, personalisation, deep learning and emerging AI technologies to create new ways for customers to discover fashion beyond traditional ecommerce experiences. You'll work on large-scale machine learning systems powering personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey. From recommendation and retrieval systems to deep learning and generative AI applications, you'll help bring innovative ideas into production and deliver experiences used by millions of customers. Working alongside Machine Learning Scientists, Software Engineers and Product Managers, you'll play a key role in designing, building and operating production ML systems at scale. You'll tackle challenging problems across recommendation systems, personalisation, deep learning and AI-powered outfit generation, helping shape the future of machine learning at ASOS. What you’ll be doing: Design, build and operate production machine learning systems that power outfit discovery and personalised fashion experiences. Partner with Machine Learning Scientists to deploy deep learning models and deliver meaningful customer and business outcomes. Deploy and optimise batch and real-time machine learning models serving millions of customers. Contribute to systems that power recommendations, personalisation and AI-driven fashion discovery experiences across ASOS. Improve system performance, reliability, observability and scalability across the machine learning lifecycle. Contribute to technical design decisions, architecture discussions and engineering best practices. Mentor and support other engineers through coaching, collaboration and knowledge sharing. Help strengthen technical practices across the team and the wider machine learning community at ASOS. Contribute to the development of shared machine learning capabilities, tools and best practices used across multiple teams. About You We're interested in candidates who bring experience in several of the following areas. We recognise that skills and expertise can be developed through a variety of experiences and career paths. Experience designing, building and deploying machine learning systems in production environments. Strong understanding of machine learning engineering principles and modern software engineering practices. Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow or similar. Experience training and optimising models using large datasets and distributed compute infrastructure. Experience working with recommendation systems, ranking, retrieval, personalisation or related machine learning domains. Knowledge of MLOps practices, including model deployment, monitoring and lifecycle management. Experience building reliable, observable and scalable services in cloud environments. Comfortable providing technical leadership and mentoring other engineers. Strong collaboration and communication skills, with experience working in cross-functional product teams. Curiosity about emerging AI technologies and the practical application of LLMs and generative AI in customer-facing products. BeneFITS’ Employee discount (hello ASOS discount!) Employee sample sales 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 Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role

We're looking for an Applied Scientist to join the team – whose mission is to build machine learning capabilities that power better decisions, experiences and outcomes across ASOS. You'll work on challenging real-world machine learning problems, developing scalable models and intelligent systems that support a range of business domains. As an Applied Scientist, you'll work alongside data engineers, ML engineers, analysts, product managers and business stakeholders to design, develop and deploy machine learning solutions at scale. You'll have the opportunity to influence both the scientific direction of our ML capabilities and the products they enable. Key Responsibilities Design, develop and deploy machine learning models and data-driven solutions in production environments. Apply machine learning and optimisation techniques to solve complex business problems. Partner with engineers to productionise models and build reliable, scalable ML systems. Design and analyse experiments and evaluation frameworks to measure model performance and business impact. Explore, evaluate and prototype new approaches from both industry and academia. Work closely with product and business stakeholders to identify opportunities where machine learning can create value. Contribute to the team's technical and scientific direction through knowledge sharing, code reviews and collaboration. Help shape best practices in machine learning, experimentation and applied research across the organisation. About You You'll enjoy applying machine learning to large-scale, real-world challenges and translating research into production systems that deliver measurable impact. We'd be particularly interested in candidates who bring experience in some of the following areas: Developing and deploying machine learning models in production environments. Applying statistics, analytics and machine learning techniques to solve complex business problems. Experience in one or more of the following areas: Developing and applying machine learning solutions to solve complex business problems. Building predictive models, intelligent systems or decision-support capabilities using large-scale data. Translating research, experimentation and analytical insights into production-ready solutions. Designing and evaluating models using appropriate performance, business and customer impact measures. Working across the end-to-end machine learning lifecycle, from problem definition and experimentation through to deployment and monitoring. Applying quantitative, statistical or optimisation techniques to support decision-making and product development. Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow or similar. Experience working with large datasets and distributed data processing systems. Strong software engineering practices, including testing, version control and maintainable code. Ability to communicate technical concepts to both technical and non-technical audiences. Curiosity, pragmatism and a willingness to learn, experiment and share knowledge. Experience bringing ML products from ideation through to production. Experience working in fast-paced, product-driven environments. Familiarity with cloud-native ML platforms and MLOps practices. Publications, open-source contributions or evidence of staying current with developments in machine learning and AI. BeneFITS’ Employee discount (hello ASOS discount!) Employee sample sales 25 days paid annual leave + an extra celebration day for a special moment Private medical care scheme Fixed Annual Payment in addition to your salary each year, it's just an extra thank you from us Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role

We're looking for a Senior iOS Engineer to join our Customer Experience team and help shape the future of one of the UK's most recognisable retail apps. At ASOS, you'll build experiences used by more than 8 million active customers worldwide, delivering features that directly impact how millions of people discover, shop and engage with fashion every day. Our iPhone and iPad apps maintain excellent App Store ratings and are built using modern iOS technologies, including the latest versions of Swift. This is an opportunity to work at genuine scale, solving complex engineering challenges while collaborating with talented product, design and engineering teams. You'll have the freedom to influence technical decisions, contribute to the evolution of our platform, and help create experiences customers genuinely love. What you'll be doing Building and delivering high-quality customer experiences used by millions of customers globally. Developing features using modern iOS technologies and engineering best practices, balancing quality, performance and scalability. Partnering closely with Product, Design and fellow Engineers to shape solutions from idea through to launch. Contributing to technical discussions, architectural decisions and continuous improvements across our iOS platform. Taking ownership of features and services, helping ensure reliability, maintainability and a seamless customer experience. Mentoring and supporting other engineers, sharing knowledge and helping raise engineering standards across the team. Using data, experimentation and customer insights to inform decisions and continuously improve the app experience. Why this role is exciting Your work will reach millions of customers around the world. You'll join a high-performing mobile engineering team with a strong focus on quality and craftsmanship. You'll work with modern technologies and contribute to the future direction of our iOS platform. You'll have real influence over technical decisions, product outcomes and customer experience. You'll help shape the next generation of shopping experiences for one of the world's leading fashion destinations. About you Experience building iOS applications using Swift and the core iOS frameworks Comfortable working with Xcode, Interface Builder and Auto Layout to create responsive user interfaces Understanding of Apple’s Human Interface Guidelines and platform design principles Knowledge of common software design patterns and architecture concepts An interest in writing clear, maintainable code and improving existing codebases Experience building apps that work well across iPhone and iPad screen sizes Familiarity with unit testing and a willingness to contribute to test coverage Experience with UI automation tools, or a desire to learn them BeneFITS’ Employee discount (hello ASOS discount!) Employee sample sales 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 Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role

What you’ll be doing As a Senior AI Engineer, you’ll help build and scale AI‑driven solutions that power asos Studios and deliver images and videos to millions of ASOS customers. This role focuses on designing reliable, responsible and high‑performing AI systems, using Deep learning embedding techniques for multimodal signal processing, and generative AI technologies such as large language models (LLMs). You’ll work closely with Studios, Machine Learning Engineers and Product teams to shape the next generation of AI-powered automation for ASOS Studios. By applying computer vision to product imagery and external visual inspiration, you’ll uncover rich styling signals and combine them with customer insights to create smarter image generation, more engaging shopping journeys and more personalised fashion experiences. Designing and developing AI solutions using LLMs and generative AI, including iterating on prompts and workflows to improve output quality Building and maintaining scalable data pipelines, applying best practices in data preparation to ensure quality and reliability Helping to standardise and reuse AI workflows, making it easier for teams across different domains to build consistently and efficiently Applying MLOps principles to AI systems, including CI/CD, monitoring, model management and feature governance Partnering with Cloud Infrastructure teams to design secure, cost‑effective environments for AI workloads Embedding ethical and responsible AI practices into development, proactively identifying and mitigating bias and risk Fine‑tuning pre‑trained models for specific use cases to improve relevance and performance Designing and contributing to evaluation frameworks for AI models, including automated testing and benchmarking to support ongoing improvement Key Skills and Experience Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision. Hands-on professional experience in fine-tuning and deploying machine learning solutions end-to-end, with a focus on deep learning for computer vision (e.g Fashion-Clip) Experience with generative AI systems, prompting, retrieval augmented generation (RAG) and fine tuning LLMs Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps Experience in taking projects from inception to production. A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams. Motivated self-starter with a desire to learn, share knowledge, and grow in a fast-paced environment. BeneFITS’ Employee discount (hello ASOS discount!) Employee sample sales 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 Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role