At a Glance
- Tasks: Build and scale ML systems for content understanding across audio, video, text, and images.
- Company: Join Spotify, a leader in music and content streaming with a focus on innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on creativity and cutting-edge technology.
- Why this job: Make a real impact on millions of users by enhancing content experiences through machine learning.
- Qualifications: Experience with ML frameworks like PyTorch or TensorFlow and strong problem-solving skills.
The predicted salary is between 70000 - 90000 € per year.
Requirements
- You have experience building and deploying machine learning systems in production.
- You are comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar.
- You have experience working with large datasets and care about data quality and evaluation.
- You are interested in or have worked with multimodal machine learning.
- You understand how to design systems that balance automation with quality and user experience.
- You are comfortable working on complex problems with evolving requirements.
- You think in systems and understand how models connect to product outcomes.
- You communicate clearly and work well across technical and non-technical teams.
What the job involves
- We’re seeking a Staff Machine Learning Engineer to build and scale foundational ML systems that power content understanding across Spotify.
- In this role, you’ll work on systems that generate deep, machine-readable understanding of content across audio, video, text, and images: enabling automation, improving quality, and unlocking new product experiences.
- This work is central to delivering safe, high-quality, and differentiated experiences for millions of listeners and creators worldwide.
- Build and scale machine learning systems that generate deep understanding of content across modalities.
- Develop models for classification, tagging, semantic understanding, and content enrichment.
- Create high quality content enrichment at scale using LLMs and agentic systems.
- Design systems that make content intelligence signals available to downstream teams and products.
- Improve automation for content quality, safety, and metadata enrichment at scale.
- Collaborate with product, policy, and engineering teams to translate content intelligence into user impact.
- Contribute to evaluation frameworks, data pipelines, and annotation systems.
- Support rapid experimentation to prototype and launch new types of content signals.
- Help improve system reliability, scalability, and performance across large datasets.
Staff Machine Learning Engineer (Content Intelligence) employer: Deepstreamtech
At Spotify, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Staff Machine Learning Engineer, you'll have the opportunity to work with cutting-edge technologies in a vibrant environment that values employee growth and development. Our commitment to diversity and inclusion, along with our focus on meaningful projects that impact millions of users globally, makes Spotify a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Machine Learning Engineer (Content Intelligence)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving PyTorch or TensorFlow. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss how you've tackled complex ML challenges in the past and how you balance automation with quality. 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 by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Staff Machine Learning Engineer (Content Intelligence)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning systems and frameworks like PyTorch or TensorFlow. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for the Staff Machine Learning Engineer role. Share your passion for content intelligence and how your past experiences can contribute to our mission at StudySmarter.
Showcase Your Problem-Solving Skills:In your application, highlight specific examples where you've tackled complex problems, especially in evolving environments. We love candidates who think in systems and can connect models to real-world outcomes!
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 any important updates from our team!
How to prepare for a job interview at Deepstreamtech
✨Know Your ML Frameworks
Make sure you brush up on your experience with ML frameworks like PyTorch and TensorFlow. Be ready to discuss specific projects where you've used these tools, focusing on the challenges you faced and how you overcame them.
✨Showcase Your Data Quality Skills
Since data quality is crucial, prepare examples that highlight your experience working with large datasets. Talk about how you ensured data integrity and the methods you used for evaluation—this will show your attention to detail.
✨Understand Multimodal Machine Learning
If you have experience with multimodal machine learning, be sure to mention it! Discuss how you've integrated different types of data (like audio, video, and text) in your projects and the impact it had on user experience.
✨Communicate Across Teams
This role requires collaboration with both technical and non-technical teams. Prepare to share examples of how you've effectively communicated complex ideas to diverse audiences, ensuring everyone is on the same page.
