# Senior Machine Learning Engineer - Policy & Safety

**Company:** [Spotify](https://hotfix.jobs/companies/spotify)
**Location:** New York, NY
**Role:** ML Engineering
**Skills:** PyTorch, Machine Learning, LLMs, Multimodal Models, Scala, Distributed Systems, Ml Evaluation, Content Moderation, Policy Enforcement, Evaluation Frameworks
**Posted:** 2026-05-04

> Designs, builds, and deploys production ML systems for content safety, moderation, and policy enforcement at Spotify scale. Leads technical initiatives, develops multimodal/LLM models, and collaborates with Trust & Safety, Legal teams on safety-critical systems.

## Job Description

## 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

- Solid experience building and deploying machine learning systems in production environments at scale
- Experienced with training, evaluating, and maintaining ML models using modern frameworks such as **PyTorch**
- Deep understanding of machine learning evaluation, including dataset design, metrics, and continuous improvement systems
- Know how to design systems that balance performance, reliability, and real-world impact in high-stakes domains
- Care about building safe, responsible, and user-centric ML systems
- Comfortable working across disciplines, partnering with legal, policy, and product stakeholders
- Experience leading technical projects and influencing direction within a team or product area
- Experience with distributed systems or backend technologies (e.g., **Scala**)

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