At a Glance
- Tasks: Design and implement advanced machine learning models for real-time recommender systems.
- Company: Leading UK fashion retailer with a focus on innovation.
- Benefits: Competitive salary, employee discounts, and professional development opportunities.
- Other info: Exciting career growth in a fast-paced, creative environment.
- Why this job: Join a dynamic team and shape the future of fashion with cutting-edge technology.
- Qualifications: Experience in deep learning and modern ML frameworks, plus a collaborative spirit.
The predicted salary is between 50000 - 65000 £ per year.
A leading fashion retailer in the UK is seeking a Machine Learning Engineer with strong expertise in developing and deploying machine learning solutions. In this role, you will work with cross-functional teams to design and implement advanced models, particularly for recommender systems.
The ideal candidate should have hands-on experience with deep learning, modern ML frameworks, and a collaborative mindset.
Additional benefits include competitive salary, employee discounts, and professional development opportunities.
ML Engineer - Recommenders (Real-Time, Scalable) employer: ASOS
As a leading fashion retailer in the UK, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration. Our employees enjoy competitive salaries, generous discounts on our products, and ample opportunities for professional growth, making it an ideal environment for those looking to make a meaningful impact in the world of machine learning and fashion.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer - Recommenders (Real-Time, Scalable)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at the company you're eyeing. A friendly chat can sometimes lead to insider info or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommender systems. This gives you a chance to demonstrate your expertise beyond just words.
✨Tip Number 3
Prepare for the interview by brushing up on your deep learning knowledge and ML frameworks. Be ready to discuss your past experiences and how they relate to the role. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace ML Engineer - Recommenders (Real-Time, Scalable)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning and recommender systems. We want to see how your skills align with the role, so don’t be shy about showcasing your deep learning projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. Let us know what excites you about working in the fashion retail space.
Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them! We love seeing practical applications of your skills, especially if they involve real-time or scalable solutions. Include links to your GitHub or portfolio if you have them.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at ASOS
✨Know Your ML Frameworks
Make sure you brush up on the modern machine learning frameworks relevant to the role, like TensorFlow or PyTorch. Be ready to discuss your hands-on experience with these tools and how you've used them to develop scalable models.
✨Showcase Your Recommender Systems Knowledge
Prepare to dive deep into your understanding of recommender systems. Think about specific projects where you've implemented these systems, the challenges you faced, and how you overcame them. This will show your expertise and problem-solving skills.
✨Collaborative Mindset is Key
Since this role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve contributed to team success in previous projects.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current projects, the team dynamics, or how they measure the success of their machine learning solutions. This demonstrates your enthusiasm and engagement.
