At a Glance
- Tasks: Develop and deploy impactful machine learning solutions for recommender systems.
- Company: Join ASOS, a leading fashion retailer in Greater London.
- Benefits: Enjoy competitive salary, performance bonuses, and professional growth opportunities.
- Why this job: Make a real impact with cutting-edge machine learning technology in a dynamic team.
- Qualifications: Hands-on experience in machine learning and a collaborative mindset.
The predicted salary is between 50000 - 65000 € per year.
ASOS in Greater London is seeking a Machine Learning Engineer to join their cross-functional team. In this role, you will develop and deploy impactful machine learning solutions, focusing currently on recommender systems.
Successful candidates will have hands-on experience in machine learning, particularly deep learning, and a collaborative mindset. The position offers competitive salary, performance-based bonuses, and opportunities for professional growth.
ML Engineer, Recommender Systems — Scale & Impact employer: ASOS
ASOS is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters collaboration and innovation. Employees benefit from competitive salaries, performance-based bonuses, and ample opportunities for professional development, making it an ideal place for those looking to make a meaningful impact in the field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer, Recommender Systems — Scale & Impact
✨Tip Number 1
Network like a pro! Reach out to current or former employees at ASOS on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects, especially those related to recommender systems. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on deep learning concepts and coding challenges. We can even set up mock interviews with friends to nail it!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can track our progress and stay updated on any new opportunities at ASOS.
We think you need these skills to ace ML Engineer, Recommender Systems — Scale & Impact
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your hands-on experience in machine learning and deep learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about recommender systems and how you can contribute to our team at ASOS. Keep it engaging and personal – we love to see your personality!
Showcase Collaboration Skills:Since this role involves working in a cross-functional team, make sure to mention any collaborative projects you've been part of. We value teamwork, so share examples that demonstrate your ability to work well with others.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at ASOS
✨Know Your ML Fundamentals
Brush up on your machine learning basics, especially deep learning concepts. Be ready to discuss algorithms, model evaluation metrics, and the intricacies of recommender systems. This will show that you have a solid foundation and can contribute effectively.
✨Showcase Your Projects
Prepare to talk about your hands-on experience with machine learning projects. Highlight specific examples where you've developed or deployed models, particularly in recommender systems. Use metrics to demonstrate the impact of your work, as this will resonate well with the interviewers.
✨Emphasise Collaboration
Since ASOS values a collaborative mindset, be ready to discuss how you've worked in cross-functional teams. Share examples of how you’ve communicated complex technical concepts to non-technical stakeholders, as this will illustrate your ability to work well within their team.
✨Ask Insightful Questions
Prepare thoughtful questions about ASOS's current projects and future goals in machine learning. This shows your genuine interest in the role and helps you understand how you can make a meaningful impact within their team.
