At a Glance
- Tasks: Design and build machine learning systems that enhance customer engagement and marketing effectiveness.
- Company: Join ASOS, a leading fashion retailer embracing innovative technology.
- Benefits: Enjoy employee discounts, flexible benefits, and 25 days of paid leave plus a celebration day.
- Other info: Opportunity for personal growth and mentoring within a collaborative team.
- Why this job: Make a real impact by shaping the future of machine learning in a dynamic environment.
- Qualifications: Experience in machine learning systems, strong Python skills, and knowledge of MLOps principles.
The predicted salary is between 63000 - 77000 £ per year.
At ASOS, machine learning is a core part of how millions of customers discover products, engage with our brand and shop every day. We're looking for a Senior Machine Learning Engineer to join our Customer & Martech team. In this role, you'll help build and scale machine learning products that support customer growth, marketing effectiveness, pricing and personalisation.
Responsibilities:
- Design, build and operate machine learning systems that support 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 closely with Applied Scientists to translate research and experimentation into scalable production systems.
- Help shape the future of our MLOps platform by contributing to engineering best practices, operational excellence and platform capabilities.
- Build reusable tooling, frameworks and infrastructure that 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.
Requirements:
- 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 working 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 areas such as 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 your immediate team.
- A track record of delivering machine-learning solutions that generated measurable customer or commercial outcomes.
Conditions:
- 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
Machine learning engineer for customer and marketing in London employer: ASOS
ASOS, the parent company of TOPSHOP and TOPMAN, is an exceptional employer that fosters a vibrant and inclusive work culture in the heart of London. With a strong commitment to employee growth, you will benefit from personalised learning opportunities and a supportive environment that encourages creativity and innovation. Enjoy competitive benefits such as generous annual leave, private medical care, and exclusive employee discounts, all while being part of a dynamic team dedicated to shaping the future of fashion.
StudySmarter Expert Advice🤫
We think this is how you could land Machine learning engineer for customer and marketing in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at ASOS or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to ASOS.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like ASOS.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like ASOS that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Machine learning engineer for customer and marketing in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at ASOS.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at ASOS and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at ASOS
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If ASOS uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.