Senior Machine Learning Engineer - Policy & Safety

What You'll Do

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Design, build, and ship production-grade machine learning systems that power content safety and policy enforcement at Spotify scale

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Own and lead key technical initiatives across detection, classification, and policy evaluation systems

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Develop and maintain ML models for content moderation, including multimodal and LLM-based systems

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Build robust evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops

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Drive experimentation to improve model performance, reliability, and fairness in safety-critical systems

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Collaborate closely with cross-functional partners in Trust & Safety, Legal, and Public Affairs to align on policy and enforcement needs

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Provide technical leadership within the team, mentoring engineers and contributing to ML strategy and prioritization

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Represent technical decisions and trade-offs in stakeholder discussions and influence product direction

Who You Are

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You have solid experience building and deploying machine learning systems in production environments at scale

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You are experienced with training, evaluating, and maintaining ML models using modern frameworks such as PyTorch

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You have a deep understanding of machine learning evaluation, including dataset design, metrics, and continuous improvement systems

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You know how to design systems that balance performance, reliability, and real-world impact in high-stakes domains

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You care about building safe, responsible, and user-centric ML systems

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You are comfortable working across disciplines, partnering with legal, policy, and product stakeholders

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You have experience leading technical projects and influencing direction within a team or product area

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You have experience with distributed systems or backend technologies (e.g., Scala)

Where You'll Be

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This role is based in New York

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We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.