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- Tasks: Design machine learning systems to enhance user recommendations and optimise satisfaction.
- Company: Join Spotify's innovative Personalization team in London.
- Benefits: Flexible remote work, inclusivity, and a chance to revolutionise listening experiences.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Make a real impact on how the world listens with cutting-edge technology.
- Qualifications: 5+ years in machine learning, data, or backend engineering, focusing on recommendation systems.
The predicted salary is between 60000 - 80000 £ per year.
Spotify is seeking experienced professionals for their Personalization team in London. The role involves designing machine learning systems that enhance user recommendations and optimize user satisfaction, working closely with cross-functional teams.
Candidates must have over 5 years of experience in machine learning, data, or backend engineering, with a focus on recommendation systems. Flexibility in remote work is offered, alongside a commitment to inclusivity.
Join Spotify to help revolutionize the way the world listens!
ML Engineer, Personalization & Real-Time Recommendations in London employer: Spotify
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer, Personalization & Real-Time Recommendations in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Spotify or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommendation systems. This is your chance to demonstrate what you can bring to the table beyond your CV.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to collaborate with cross-functional teams at Spotify.
✨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 are proactive about their job search!
We think you need these skills to ace ML Engineer, Personalization & Real-Time Recommendations in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and recommendation systems. 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 personalisation and real-time recommendations. We love seeing candidates who can connect their experiences to our mission at Spotify.
Showcase Your Teamwork Skills: Since this role involves working closely with cross-functional teams, make sure to mention any collaborative projects you've been part of. We value teamwork, so let us know how you’ve contributed to group success!
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’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Spotify
✨Know Your ML Fundamentals
Make sure you brush up on your machine learning fundamentals, especially around recommendation systems. Be ready to discuss algorithms you've used and how they impacted user satisfaction. Spotify will want to see that you can not only design systems but also understand the theory behind them.
✨Showcase Your Experience
With over 5 years of experience required, be prepared to share specific projects where you've designed or optimised machine learning systems. Use metrics to demonstrate your impact, like improved user engagement or satisfaction scores. This will help you stand out as a candidate who delivers results.
✨Collaborate Like a Pro
Since the role involves working closely with cross-functional teams, highlight your collaboration skills. Share examples of how you've successfully worked with data scientists, engineers, or product managers in the past. Spotify values inclusivity, so showing that you can work well with diverse teams is key.
✨Ask Insightful Questions
Prepare thoughtful questions about Spotify's approach to personalisation and real-time recommendations. This shows your genuine interest in the role and the company. It’s also a great way to gauge if their culture aligns with your values, especially regarding flexibility and inclusivity.