At a Glance
- Tasks: Design and build machine learning systems for content safety at Spotify scale.
- Company: Join Spotify's innovative Policy & Safety team, ensuring a safe platform for millions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with a focus on safety, compliance, and cross-functional teamwork.
- Why this job: Make a real impact on user safety while working with cutting-edge ML technologies.
- Qualifications: Experience in ML systems, strong collaboration skills, and leadership in technical projects.
The predicted salary is between 80000 - 100000 € per year.
Requirements
- 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).
What the job involves
- 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.
- 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.
Senior Machine Learning Engineer (Policy & Safety) in London employer: Deepstreamtech
At Spotify, we pride ourselves on being an exceptional employer, particularly for our Senior Machine Learning Engineer role within the Policy & Safety team. Our collaborative work culture fosters innovation and inclusivity, allowing you to partner with diverse teams while contributing to meaningful projects that ensure user safety and compliance. With ample opportunities for professional growth and a commitment to building responsible ML systems, you'll find a rewarding environment that values your expertise and encourages continuous learning.
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 already at Spotify or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that highlight your experience with PyTorch and real-world applications. This is your chance to shine beyond the CV!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've tackled challenges in ML systems and how you collaborate with cross-functional teams. We want to see your problem-solving skills in action!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at StudySmarter and contributing to something great.
We think you need these skills to ace Senior Machine Learning Engineer (Policy & Safety) in London
Some tips for your application 🫡
Show Off Your Experience:Make sure to highlight your solid experience in building and deploying machine learning systems. We want to see how you've tackled real-world challenges, so share specific examples of your work with frameworks like PyTorch.
Focus on Safety and User-Centric Design:Since we're all about building safe and responsible ML systems, emphasise your understanding of safety in machine learning. Talk about how you've designed systems that prioritise user safety and compliance in high-stakes environments.
Collaboration is Key:We love team players! Mention any experiences where you've worked across disciplines, especially with legal or policy teams. Show us how you’ve influenced project direction and collaborated to achieve common goals.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Deepstreamtech
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around frameworks like PyTorch. Be ready to discuss your experience with building and deploying ML systems in production environments, as well as how you've evaluated and maintained models.
✨Understand the Bigger Picture
Since this role involves working closely with legal and policy teams, it’s crucial to understand how machine learning intersects with compliance and safety. Familiarise yourself with the concepts of content moderation and policy enforcement, and be prepared to discuss how you can contribute to these areas.
✨Showcase Your Leadership Skills
This position requires technical leadership, so think about examples where you've led projects or influenced team direction. Be ready to share how you've mentored others and contributed to ML strategy, as this will demonstrate your ability to take charge in a collaborative environment.
✨Prepare for Technical Discussions
Expect to dive deep into technical discussions about system design, performance, and reliability. Brush up on distributed systems and backend technologies like Scala, and be prepared to discuss how you would approach designing safe and user-centric ML systems in high-stakes domains.
