At a Glance
- Tasks: Drive machine learning strategy for safety and compliance at Spotify.
- Company: Join Spotify, a leader in music streaming with a focus on user experience.
- Benefits: Flexible work environment, competitive salary, and opportunities for professional growth.
- Other info: Collaborative culture with mentorship opportunities and a focus on innovation.
- Why this job: Shape the future of content safety and policy enforcement on a global scale.
- Qualifications: Experience in building production-grade ML systems and modern frameworks like PyTorch or TensorFlow.
The predicted salary is between 80000 - 100000 £ 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.
The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continues to grow, driven by advances in AI and new creation tools—we’re investing in systems that ensure content remains safe, compliant, and high quality.
We’re seeking a Senior Staff Machine Learning Engineer to build and scale ML systems that power safety, policy enforcement, and compliance across Spotify. In this role, you’ll shape how automated systems evaluate and act on content—ensuring decisions are consistent, explainable, and reliable at global scale. This work is critical to maintaining trust for both listeners and creators.
What You Will Do
- Define & drive machine learning strategy for safety, policy enforcement, and compliance systems
- Build and scale ML systems for detection, classification, and risk assessment across content
- Develop automated decisioning systems that ensure consistent, reliable enforcement of policies
- Design systems that support real-time and large-scale content evaluation
- Collaborate with product, policy, and trust & safety teams to operationalize content standards
- Improve automation to reduce manual intervention, maintaining high quality and safety standards
- Drive best practices in evaluation, fairness, and system reliability
- Mentor engineers and contribute to technical direction across teams
Who You Are
- You have strong experience building production-grade machine learning systems at scale
- You are experienced with modern ML frameworks such as PyTorch, TensorFlow, or similar
- You have worked on systems where ML outputs influence real-world decisions
- You understand how to design systems that balance automation with safety and user experience
- You are comfortable working on complex, ambiguous problems with high impact
- You think in systems and understand how models connect to platform-level outcomes
- You care about data quality, evaluation rigor, and system reliability
- You communicate clearly and influence across technical and non-technical teams
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.
Senior Staff Machine Learning Engineer - Content Policy & Safety in Stockholm employer: Spotify
At Spotify, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. As a Senior Product Manager for our design systems, you'll have the opportunity to shape the future of product development while working in a vibrant city like Stockholm, known for its creativity and tech-forward mindset. We offer flexible working arrangements, a commitment to employee growth through continuous learning, and a supportive environment where your contributions directly impact the user experience across our platform.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Staff Machine Learning Engineer - Content Policy & Safety in Stockholm
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Spotify or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Spotify.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Spotify.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Spotify that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Staff Machine Learning Engineer - Content Policy & Safety in Stockholm
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Spotify.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Spotify and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Spotify
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Spotify uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
