Senior Machine Learning Engineer - Policy & Safety
Spotify · New York, NY · 3 wk ago
EngineeringFull-time
What You'll Do
- 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
Who You Are
- 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)