At a Glance
- Tasks: Design and build machine learning systems for content safety at Spotify scale.
- Company: Join Spotify, a leader in creating effortless and joyful listening experiences.
- Benefits: Flexible work options, competitive salary, and opportunities for professional growth.
- Other info: Work in a supportive team with excellent career advancement opportunities.
- Why this job: Make a real impact on user safety and policy enforcement in a dynamic environment.
- Qualifications: Experience in deploying ML systems and collaborating across disciplines.
The predicted salary is between 80000 - 100000 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.
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 London employer: Spotify
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - Policy & Safety in London
✨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 a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects related to machine learning, make sure to highlight them during interviews. It’s all about demonstrating what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail.
✨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 Senior Machine Learning Engineer - Policy & Safety in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your experience with machine learning systems, especially in production environments, and don’t forget to mention any relevant projects you've led.
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for the role. Explain why you’re excited about working at Spotify and how your background in ML and policy enforcement can contribute to our mission of creating safe and enjoyable user experiences.
Showcase Your Technical Skills: When detailing your technical skills, be specific! Mention your experience with frameworks like PyTorch and any projects where you’ve built or maintained ML models. We want to see how you’ve tackled challenges in high-stakes domains and what impact your work has had.
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’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Spotify
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around the frameworks mentioned in the job description like PyTorch. Be ready to discuss your experience with building and deploying ML systems, as well as how you've tackled challenges in production environments.
✨Understand Content Safety
Familiarise yourself with content moderation and policy enforcement systems. Think about how you can contribute to making Spotify a safer platform. Prepare examples of how you've approached safety-critical systems in the past and be ready to discuss your thoughts on user-centric ML.
✨Collaboration is Key
This role involves working closely with various teams like Trust & Safety and Legal. Be prepared to talk about your experience collaborating across disciplines. Share specific examples of how you've influenced product direction or led technical projects in a team setting.
✨Show Your Leadership Skills
As a senior engineer, you'll need to demonstrate your ability to lead and mentor others. Think of instances where you've taken the lead on a project or helped a colleague grow their skills. Highlight your approach to technical decision-making and how you balance performance with real-world impact.