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) employer: Deepstreamtech
Spotify is an exceptional employer for a Senior Machine Learning Engineer, offering a dynamic work culture that prioritises safety and user-centric design. With a strong commitment to employee growth, you will have the opportunity to lead innovative projects at the forefront of machine learning and regulatory compliance, all while collaborating with diverse teams across the organisation. Located in a vibrant tech hub, Spotify fosters an inclusive environment where your contributions directly impact millions of users, making it a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer (Policy & Safety)
✨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 insider info on what they’re really looking for.
✨Tip Number 2
Show off your skills! If you’ve got projects or contributions that highlight your machine learning expertise, don’t be shy. Share them on platforms like GitHub or even your own website to catch the eye of recruiters.
✨Tip Number 3
Prepare for interviews by diving deep into the specifics of the role. Brush up on your knowledge of ML frameworks like PyTorch and be ready to discuss how you’d tackle real-world challenges in safety and compliance.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the StudySmarter family and contributing to our mission.
We think you need these skills to ace Senior Machine Learning Engineer (Policy & Safety)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning systems, especially in production environments. We want to see how you've used frameworks like PyTorch and your understanding of evaluation metrics.
Showcase Your Projects:Include specific examples of projects where you've led technical initiatives or collaborated with cross-functional teams. This will help us understand your impact and how you balance performance and reliability in high-stakes domains.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to read and directly related to the job description. Avoid jargon unless it's necessary!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to showcase your skills to the right people.
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.
✨Showcase Your Collaboration Skills
Since this role involves working with legal, policy, and product teams, be prepared to share examples of how you've successfully collaborated across disciplines. Highlight any projects where you influenced direction or led technical initiatives.
✨Emphasise Safety and Responsibility
This position is all about building safe and user-centric ML systems. Think of specific instances where you've prioritised safety in your work, and be ready to discuss how you balance performance with reliability in high-stakes domains.
✨Prepare for Technical Leadership Questions
As a senior engineer, you'll need to demonstrate your leadership skills. Prepare to talk about how you've mentored others, contributed to ML strategy, and made technical decisions that impacted your team or product area.
