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- Tasks: Design and build innovative audio experiences using machine learning and AI.
- Company: Join Spotify's Personalization team, shaping the future of music and podcasts.
- Benefits: Flexible work environment, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative team atmosphere with a focus on diversity and inclusion.
- Why this job: Make a real impact on millions of listeners with cutting-edge technology.
- Qualifications: Experience in machine learning, natural language processing, and building scalable systems.
The predicted salary is between 60000 - 80000 £ per year.
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
You’ll join the Horizon Product Area within the Sessions Studio, part of Spotify’s Personalization Mission. This team focuses on inventing and evolving new listening experiences powered by emerging technologies. From AI DJ to promptable playlists and generated podcasts, we’re exploring how agentic systems and generative AI can reshape how people interact with audio. You’ll work at the intersection of product innovation and cutting‑edge machine learning to bring entirely new experiences to life for millions of listeners.
What You'll Do
- Design, build, evaluate, and ship agentic based features and interactive experiences to bring our products to the next level.
- Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways.
- Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users.
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
- Actively contribute to a strong community of machine learning practitioners at Spotify.
Who You Are
- An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment.
- Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications.
- Hands‑on expertise with implementing end-to-end production ML systems at scale. Experience with production LLM scale based systems is a plus.
- Experience with incorporating human feedback to improve LLM based systems using techniques like DPO, KTO, and reinforcement fine-tuning.
- Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams.
- Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS.
Where You'll Be
We offer you the flexibility to work where you work best! For this role, you can be within the European region as long as we have a work location. This team operates within the GMT/CET time zone for collaboration, excluding France due to on‑call restrictions.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Machine Learning Engineer - Personalization, Horizon in London employer: Creandum
Contact Detail:
Creandum Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Personalization, Horizon in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Spotify. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for the interview by brushing up on your ML knowledge and understanding Spotify's products. Tailor your examples to show how you can contribute to their mission of personalisation.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the Spotify family.
We think you need these skills to ace Machine Learning Engineer - Personalization, Horizon in London
Some tips for your application 🫡
Show Your Passion for Personalisation: When you're writing your application, let us see your enthusiasm for personalisation and how it can enhance the listening experience. Share any relevant projects or experiences that highlight your understanding of user needs and how you can contribute to our mission.
Highlight Your Technical Skills: Make sure to showcase your expertise in machine learning, natural language processing, and generative AI. We want to know about your hands-on experience with production ML systems and any specific tools you've used, like Apache Beam or AWS. Be clear and concise!
Collaborate and Communicate: Since you'll be working with cross-functional teams, emphasise your collaboration skills in your application. Share examples of how you've successfully worked with designers, data scientists, and product managers to bring ideas to life. Communication is key!
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 gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Creandum
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially around natural language processing and generative AI. Be ready to discuss how you've applied these theories in real-world applications, as this role is all about bringing innovative features to life.
✨Showcase Collaboration Skills
This position involves working with cross-functional teams, so be prepared to share examples of how you've successfully collaborated with product managers, designers, and data scientists in the past. Highlight any projects where teamwork led to a successful outcome.
✨Demonstrate Problem-Solving Abilities
Think of complex problems you've tackled in your previous roles and be ready to explain your thought process. Spotify values innovation, so showing how you approached challenges and prototyped solutions will set you apart.
✨Familiarise Yourself with Tools
Get comfortable with large-scale data processing frameworks like Apache Beam or Spark, and cloud platforms such as GCP or AWS. Being able to discuss your hands-on experience with these tools will show that you're ready to hit the ground running.