Senior Machine Learning Engineer - Policy & Safety in Stockholm

Senior Machine Learning Engineer - Policy & Safety in Stockholm

Stockholm Full-Time 80000 - 100000 £ / year (est.) Working from home possible
Spotify

At a Glance

  • Tasks: Design and build machine learning systems for content safety at Spotify scale.
  • 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 focus on safety and innovation.
  • Why this job: Make a real impact on user safety and policy enforcement in a dynamic tech environment.
  • Qualifications: Experience in deploying ML systems and collaborating across disciplines.

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 Policy & Safety team sits within Content Platform in the Experience Mission, building the systems that keep Spotify safe, compliant, and trusted by millions of users and creators. This team owns Spotify’s content moderation infrastructure — from detection models to policy enforcement systems and compliance data pipelines. Working at the intersection of machine learning, platform engineering, and regulatory compliance, the team partners closely with Trust & Safety, Legal, and Public Affairs. They’re on the critical path for every new content type and social feature — including messaging, comments, and collaborative experiences — ensuring safety is built in from day one. With a strong focus on “safety by default,” the team is investing in large-scale rearchitecture and ML-driven systems to proactively protect users and empower safer interactions across the platform.

What You'll Do

  • Design, build, and ship production-grade machine learning systems that power content safety and policy enforcement at Spotify scale
  • Own and lead key technical initiatives across detection, classification, and policy evaluation systems
  • Develop and maintain ML models for content moderation, including multimodal and LLM-based systems
  • Build robust evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops
  • Drive experimentation to improve model performance, reliability, and fairness in safety-critical systems
  • Collaborate closely with cross-functional partners in Trust & Safety, Legal, and Public Affairs to align on policy and enforcement needs
  • Provide technical leadership within the team, mentoring engineers and contributing to ML strategy and prioritization
  • Represent technical decisions and trade-offs in stakeholder discussions and influence product direction

Who You Are

  • You have solid experience building and deploying machine learning systems in production environments at scale
  • You are experienced with training, evaluating, and maintaining ML models using modern frameworks such as PyTorch
  • You have a deep understanding of machine learning evaluation, including dataset design, metrics, and continuous improvement systems
  • You know how to design systems that balance performance, reliability, and real-world impact in high-stakes domains
  • You care about building safe, responsible, and user-centric ML systems
  • You are comfortable working across disciplines, partnering with legal, policy, and product stakeholders
  • You have experience leading technical projects and influencing direction within a team or product area
  • You have experience with distributed systems or backend technologies (e.g., Scala)

Where You'll 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 Machine Learning Engineer - 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.

Spotify

Contact Details:

Spotify Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Machine Learning Engineer - 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.

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We think you need these skills to ace Senior Machine Learning Engineer - Policy & Safety in Stockholm

Machine Learning Systems
Content Moderation
Policy Enforcement
ML Model Development
Multimodal Systems
LLM-based Systems
Evaluation Frameworks

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.