Senior Machine Learning Engineer (Policy & Safety) – London / Stockholm | Visa + Salary Insights

📍 Location: gb

🏷 Type: Not specified

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Job Overview

This role sits at the intersection of Machine Learning Engineering, Trust & Safety systems, and large-scale platform infrastructure. The Senior Machine Learning Engineer (Policy & Safety) at Spotify is responsible for building and scaling intelligent systems that detect, classify, and enforce content policies across one of the world’s largest audio platforms. The ideal candidate is a Senior-level ML Engineer (5+ years) with strong experience in production-grade ML systems, evaluation frameworks, and safety-critical decision systems. This position is highly cross-functional, requiring collaboration with Legal, Public Affairs, and Trust & Safety teams.

🌍 Work Eligibility & Location

This role is designed for professionals based in or willing to relocate to London (Hybrid) or Stockholm (Hybrid). While Spotify is globally distributed, this specific function requires close alignment with policy, legal, and safety operations teams, which are concentrated in Europe. Visa sponsorship is not guaranteed but may be considered depending on candidate profile and strategic need.

💰 Salary Intelligence

Compensation aligns with top-tier European tech companies for Senior Machine Learning Engineers working in high-impact safety systems. Total compensation may include bonuses, stock units, and benefits. Given the critical nature of policy enforcement ML systems, this role is positioned in the upper compensation band for applied ML roles.

📊 Role Breakdown

This position focuses on building and scaling machine learning systems for content moderation and policy enforcement across Spotify’s ecosystem. The engineer will design ML pipelines that support multimodal detection models, including text, audio, and LLM-based classifiers. A major part of the role involves developing evaluation frameworks that measure model performance, fairness, and reliability in real-time production environments. These systems must operate at Spotify scale, handling millions of content interactions daily.

The engineer will also lead initiatives around model deployment optimization, ensuring low-latency inference and robust rollback strategies. Tools such as PyTorch will be used for model development, while backend components may leverage distributed systems frameworks, including Scala-based services. Approximately 40% of the role involves hands-on ML development, 30% system design and evaluation, and 30% cross-functional collaboration with Trust & Safety, Legal, and Public Affairs teams.

A strong emphasis is placed on building safe, explainable, and policy-aligned AI systems, ensuring compliance with evolving global regulations.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly selective role requiring deep expertise in production ML engineering and real-world safety systems. Candidates must demonstrate strong technical ownership and experience working in high-stakes environments where model decisions directly affect user safety and regulatory compliance.

🚀 Career Impact

This role offers strong long-term impact in AI safety engineering and large-scale ML system design. Engineers gain exposure to regulatory-grade ML systems, multimodal model deployment, and global policy enforcement infrastructure, positioning them for senior leadership roles in AI safety and platform integrity.

📋 Key Responsibilities

The Senior ML Engineer will be responsible for designing and deploying content moderation ML models that detect harmful or policy-violating content across Spotify. Core responsibilities include building classification systems, optimizing real-time inference pipelines, and improving detection accuracy using iterative model training.

A key focus is developing evaluation frameworks that include offline benchmarking datasets and online A/B testing systems. The engineer will also implement LLM-based moderation systems and multimodal classifiers. Collaboration with policy teams ensures that ML systems reflect evolving legal and safety standards. Additionally, the role involves mentoring junior engineers and contributing to long-term ML infrastructure strategy.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

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🧠 Fit & Positioning Analysis

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📅 Application Signals

This role is high urgency due to Spotify’s ongoing expansion of safety systems and regulatory compliance infrastructure. Competition is extremely high, as candidates are drawn from global ML, AI safety, and trust & safety engineering pools. Early application increases visibility before pipeline saturation.

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✅ Job Source & Verification

This job listing is sourced from Spotify’s official engineering careers page, ensuring high credibility and authenticity. The information reflects the latest available posting and is aligned with Spotify’s hiring standards for ML engineering roles in Policy & Safety. Last updated: May 2026.