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- Tasks: Build and scale machine learning systems for content safety and policy enforcement.
- Company: Join Spotify, a leader in creating joyful listening experiences for billions.
- Benefits: Flexible work environment, competitive salary, and opportunities for professional growth.
- Other info: Work from London or Stockholm with a mix of remote and in-person meetings.
- Why this job: Make a real impact on user safety while working with cutting-edge technology.
- Qualifications: Experience in building production-grade ML systems and collaborating across teams.
The predicted salary is between 70000 - 90000 ÂŁ per year.
We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
About the Team
The Policy & Safety team sits within the Content Platform domain and builds the systems that keep Spotify safe and trustworthy at scale. We own the infrastructure behind content moderation, including detection models, policy enforcement systems, compliance pipelines, and the safety-by-default platform. Our work is critical to every new content type and product experience—from messaging and comments to collaborative and emerging AI-driven features. We partner closely with Trust & Safety, Legal, and Public Affairs to ensure that safety is built into Spotify experiences from the start.
What You Will Do
- Build and scale machine learning systems for proactive content detection, classification, and pre‑publish safety scanning
- Design and implement policy evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops
- Develop multimodal models that combine text, audio, image, and video signals for safety and policy enforcement
- Architect feedback loops that turn reviewer input into structured training data for continuous model improvement
- Translate regulatory requirements into scalable ML system designs, including accuracy and reporting expectations
- Partner with cross‑functional teams across Trust & Safety, Legal, Public Affairs, and Product to deliver safe user experiences
- Drive technical direction in ambiguous problem spaces and contribute to long‑term platform architecture
- Mentor and support other machine learning engineers, helping grow technical capability across the team
Who You Are
- You have experience building and shipping production‑grade machine learning systems at scale
- You are experienced with ML evaluation, including dataset design, metrics, and model performance monitoring
- You have worked with multimodal machine learning across text, audio, image, or video domains
- You have experience with human‑in‑the‑loop systems, active learning, or feedback‑driven model improvement
- You are comfortable translating complex requirements into technical solutions, including policy or regulatory constraints
- You are experienced working across teams and influencing technical direction in large systems
- You are comfortable navigating ambiguity and making thoughtful trade‑offs between speed, quality, and risk
- You communicate clearly and collaborate effectively with both technical and non‑technical partners
Where You Will Be
This role is based in London or Stockholm. We offer you the flexibility to work where you work best! There will be some in‑person meetings, but still allows for flexibility to work from home.
Staff Machine Learning Engineer - Safety & Policy employer: Creandum
Contact Detail:
Creandum Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Engineer - Safety & Policy
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Spotify. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or projects that highlight your machine learning expertise, make sure to share them during interviews or networking events.
✨Tip Number 3
Prepare for those tricky questions! Brush up on your technical knowledge and be ready to discuss how you’d tackle real-world problems related to safety and policy in machine learning.
✨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, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Staff Machine Learning Engineer - Safety & Policy
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff Machine Learning Engineer role. Highlight your experience with machine learning systems, especially in safety and policy contexts, to show us you’re a great fit!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re passionate about this role at Spotify. Share specific examples of your work with multimodal models or human-in-the-loop systems, and how they relate to our mission of creating safe user experiences.
Showcase Your Collaboration Skills: Since this role involves working closely with cross-functional teams, make sure to mention any past experiences where you’ve successfully collaborated with non-technical partners. We love seeing how you can bridge the gap between tech and other areas!
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 during the process. Let’s get started on this journey together!
How to prepare for a job interview at Creandum
✨Know Your Stuff
Make sure you brush up on your machine learning knowledge, especially around building and scaling production-grade systems. Be ready to discuss your experience with multimodal models and how you've tackled complex problems in the past.
✨Showcase Your Collaboration Skills
Since this role involves working closely with cross-functional teams, prepare examples of how you've successfully collaborated with non-technical partners. Highlight any experiences where you influenced technical direction or navigated ambiguity.
✨Prepare for Technical Questions
Expect to dive deep into ML evaluation metrics and dataset design. Be ready to explain your approach to model performance monitoring and how you've implemented feedback loops in previous projects.
✨Communicate Clearly
Practice explaining complex concepts in simple terms. The interviewers will want to see how well you can communicate with both technical and non-technical stakeholders, so think about how you can make your points clear and engaging.