At a Glance
- Tasks: Build and scale machine learning systems for content safety and policy enforcement.
- Company: Join Spotify, the world's leading audio streaming service with a focus on user experience.
- Benefits: Flexible work options, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with opportunities to mentor and grow your skills.
- Why this job: Make a real impact on user safety while working with cutting-edge technology.
- Qualifications: Experience in machine learning systems and strong collaboration skills required.
The predicted salary is between 70000 - 90000 € 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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Staff Machine Learning Engineer - Policy & Safety employer: Spotify
Spotify is an exceptional employer that fosters a culture of innovation and collaboration, particularly within the Policy & Safety team. With a focus on building safe and trustworthy user experiences, employees benefit from flexible working arrangements in vibrant locations like London or Stockholm, alongside opportunities for professional growth through mentorship and cross-functional partnerships. Join us to be part of a mission that transforms complex challenges into intuitive solutions for millions of users worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Machine Learning Engineer - Policy & Safety
✨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 a job description just 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. Real-world examples speak volumes.
✨Tip Number 3
Prepare for the interview by diving deep into Spotify's mission and values. Tailor your answers to show how your experience aligns with making listening effortless and safe for users.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Staff Machine Learning Engineer - Policy & Safety
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 content detection and policy enforcement.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about building safe user experiences. Share specific examples of how you've tackled complex problems in previous roles, especially in ambiguous situations.
Showcase Your Collaboration Skills:Since this role involves working with cross-functional teams, emphasise your ability to communicate effectively with both technical and non-technical partners. Give examples of successful collaborations in your past projects.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Spotify
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning fundamentals, especially around building and scaling production-grade systems. Be ready to discuss your experience with multimodal models and how you've tackled challenges in content detection and classification.
✨Understand the Policy & Safety Landscape
Familiarise yourself with the regulatory requirements and safety policies relevant to Spotify. Think about how you can translate these into scalable ML system designs and be prepared to share examples of how you've done this in the past.
✨Show Off Your Collaboration Skills
This role involves working closely with cross-functional teams, so be ready to talk about your experience collaborating with non-technical partners. Highlight any instances where you influenced technical direction or navigated ambiguity in large systems.
✨Prepare for Technical Challenges
Expect some technical questions that may involve problem-solving on the spot. Practice articulating your thought process clearly, especially when discussing trade-offs between speed, quality, and risk in your previous projects.
