Associate Machine Learning Engineer, Trust & Safety Intelligence

Remote

Job Description

The Trust & Safety Intelligence team builds technology that keeps Spotify a safe and welcoming space for creativity. We design and scale AI systems that detect harmful or risky activity, uphold global compliance standards, and make moderation operations more efficient. The team is also expanding how we use GenAI to support policy specialists who work around the clock to protect our users from harm. Together, we’re building a strong foundation for safe and responsible innovation at Spotify.

As an Associate Machine Learning Engineer, you will help develop AI and ML systems that improve how Spotify detects, reviews, and manages risky or non-compliant activity. You’ll work with engineers, data scientists, and policy partners to design and evaluate models, automate performance tracking, and enhance transparency and auditability. This is a hands-on, collaborative role where you’ll learn from experienced practitioners while building solutions that advance safety, compliance, and responsible innovation.

What You'll Do

Build and evaluate ML models that identify, prioritize, and mitigate harmful or risky behavior on the platform

Support model monitoring and performance tracking to ensure reliability, transparency, and accountability

Develop scalable ML pipelines using standard best practices for model development and deployment

Explore emerging GenAI tools and frameworks to identify practical, compliant use cases that improve workflow efficiency

Communicate results clearly and document technical decisions to promote shared understanding across teams

Collaborate with cross-functional partners in engineering, data, policy, and product to align technical outcomes with safety and compliance goals

Who You Are

You’re passionate about using AI to make digital spaces safer and more inclusive

You have a working knowledge of machine learning fundamentals and hands-on experience with Python and modern ML frameworks like PyTorch or TensorFlow

You have experience working with large datasets, model evaluation, and data exploration in SQL or similar tools

You have knowledge and/or experience building workflows that integrate LLMs and data into autonomous, multi-step workflows

You collaborate well with others and communicate clearly across disciplines

You have 1+ years of experience (academic or professional) applying ML, NLP, or data science methods to real-world problems

You’re eager to learn continuously, refine your craft, and contribute to technology that makes a real impact

Where You'll Be

We offer you the flexibility to work where you work best! For this role, you can be within the United States region as long as we have a work location.

This team operates within the Eastern Time Zone for collaboration.

The United States base range for this position is $68,526 - $97,894, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.

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