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- Tasks: Design and build machine learning systems for content safety and policy enforcement.
- Company: Join Spotify, a leading tech company with a focus on innovation.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Other info: Enjoy a dynamic work environment with a focus on collaboration and creativity.
- Why this job: Make a real impact on content safety while working with cutting-edge ML technology.
- Qualifications: Experience in ML systems, proficiency in PyTorch, and strong technical leadership skills.
The predicted salary is between 70000 - 90000 £ per year.
Spotify is looking for a skilled professional to design and build production-grade machine learning systems for content safety and policy enforcement. The role involves developing ML models, driving technical initiatives, and collaborating closely with various stakeholders.
The ideal candidate has a solid background in ML systems at scale, is experienced with frameworks like PyTorch and has strong technical leadership.
The position is based in London with flexible work-from-home options.
Senior ML Engineer, Policy & Safety — Remote‑Flexible employer: Spotify
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer, Policy & Safety — Remote‑Flexible
✨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 might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving content safety or policy enforcement. This will demonstrate your expertise and passion for the role.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of ML frameworks like PyTorch. Practice coding challenges and system design questions to impress the hiring team with your technical prowess.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior ML Engineer, Policy & Safety — Remote‑Flexible
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML systems and frameworks like PyTorch. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about content safety and policy enforcement. We love seeing candidates who can connect their personal interests with our mission.
Showcase Technical Leadership: If you've led technical initiatives or collaborated with stakeholders in the past, make sure to mention that! We value strong leadership skills, so share examples of how you've driven projects forward.
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’s super easy!
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 production-grade systems. Be ready to discuss your experience with frameworks like PyTorch and any specific projects you've worked on that relate to content safety and policy enforcement.
✨Showcase Your Leadership Skills
Since this role involves technical leadership, prepare examples of how you've led initiatives in the past. Think about times when you collaborated with stakeholders or drove a project from concept to completion, and be ready to share those stories.
✨Understand Spotify's Culture
Familiarise yourself with Spotify's values and culture. They appreciate innovation and collaboration, so think about how your personal values align with theirs. This will help you demonstrate that you're not just a fit for the role, but also for the company.
✨Prepare Questions
Have a few thoughtful questions ready to ask at the end of your interview. This shows your interest in the role and helps you gauge if it's the right fit for you. Consider asking about their current ML projects or how they measure success in this position.