At a Glance
- Tasks: Build and scale machine learning systems for content safety and policy enforcement.
- Company: Join Spotify's innovative Policy & Safety team, ensuring a safe user experience.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with mentorship opportunities and a focus on continuous improvement.
- Why this job: Make a real impact on user safety while working with cutting-edge multimodal technologies.
- Qualifications: Experience in machine learning systems, strong collaboration skills, and ability to navigate ambiguity.
The predicted salary is between 80000 - 100000 £ per year.
Requirements
- 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.
What the job involves
- 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.
- 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.
Senior ML Engineer - Safety & Policy (Multimodal) in London employer: Spotify
At Spotify, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior ML Engineer in our Policy & Safety team, you'll have the opportunity to work on cutting-edge machine learning systems that ensure user safety while enjoying a supportive environment that encourages professional growth and mentorship. Located in a vibrant tech hub, we offer competitive benefits and a commitment to diversity, making Spotify a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Engineer - Safety & Policy (Multimodal) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Spotify or similar companies. 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 built any cool ML projects, make sure to showcase them. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms—this will help you connect with both technical and non-technical interviewers.
✨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 our team.
We think you need these skills to ace Senior ML Engineer - Safety & Policy (Multimodal) in London
Some tips for your application 🫡
Show Off Your Experience:Make sure to highlight your experience with building and shipping production-grade machine learning systems. We want to see how you've tackled challenges in the past, especially in multimodal contexts like text, audio, and video.
Be Clear and Concise:When translating complex requirements into technical solutions, clarity is key. Use straightforward language to explain your thought process and how you approach ambiguity. We appreciate a well-structured application!
Collaborate Like a Pro:Since you'll be working with various teams, emphasise your collaboration skills. Share examples of how you've influenced technical direction and worked effectively with both technical and non-technical partners.
Apply Through Our Website:We encourage you to apply 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 ML Systems Inside Out
Make sure you can talk confidently about your experience building and shipping production-grade machine learning systems. Be ready to discuss specific projects where you've tackled challenges related to scale, performance monitoring, and evaluation metrics.
✨Showcase Your Multimodal Expertise
Prepare examples of how you've worked with multimodal machine learning across different domains like text, audio, and video. Highlight any innovative approaches you've taken to integrate these modalities into cohesive models, especially in safety and policy contexts.
✨Communicate Clearly About Complex Requirements
Practice explaining complex technical concepts in simple terms. You’ll need to demonstrate your ability to translate regulatory constraints into actionable solutions, so think of scenarios where you've successfully navigated ambiguity and made trade-offs.
✨Collaborate and Influence Across Teams
Be ready to share experiences where you've worked with cross-functional teams, such as Trust & Safety or Legal. Discuss how you influenced technical direction and contributed to long-term architecture, showcasing your collaborative spirit and leadership skills.
