Home › Companies › Spotify › Senior Machine Learning Engineer - Policy & Safety
Senior Machine Learning Engineer - Policy & Safety
Spotify · New York, NY · Hybrid · Active · Lever
Job facts
| Field | Value |
|---|---|
| Company | Spotify |
| Title | Senior Machine Learning Engineer - Policy & Safety |
| Normalized title | - |
| Department / team | Engineering / Experience |
| Location | New York, NY, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Permanent |
| Salary | - |
| Status | active |
| ATS provider | Lever |
| Posted / first seen | 2026-05-04 / 2026-05-29 |
| Changed / last seen | 2026-06-23 / 2026-06-23 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Spotify. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Lever. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in Engineering. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Spotify |
| Source | 8f76458c-d40f-4324-bb14-bb757d1b7058 |
| ATS provider | Lever |
Description
We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
The Policy & Safety team sits within Content Platform in the Experience Mission, building the systems that keep Spotify safe, compliant, and trusted by millions of users and creators. This team owns Spotify’s content moderation infrastructure — from detection models to policy enforcement systems and compliance data pipelines.
Working at the intersection of machine learning, platform engineering, and regulatory compliance, the team partners closely with Trust & Safety, Legal, and Public Affairs. They’re on the critical path for every new content type and social feature — including messaging, comments, and collaborative experiences — ensuring safety is built in from day one. With a strong focus on “safety by default,” the team is investing in large-scale rearchitecture and ML-driven systems to proactively protect users and empower safer interactions across the platform.
The United States base range for this position is $184,050 - $262,928 USD, 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, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
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)
Where You'll Be
This role is based in New York
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.
Full job record
| Job ID | eb3c3d06dc79c9d433f63343e335c4e7b26563c5 |
| Org ID | 72fe3b06-0d08-4f7d-9dfd-beedeeda0a25 |
| Source ID | 8f76458c-d40f-4324-bb14-bb757d1b7058 |
| Board ID | 8f76458c-d40f-4324-bb14-bb757d1b7058 |
| Provider | lever |
| Provider Job Key | 9eca14d3-8e0b-46de-8161-704e07f3d9d0 |
| Title | Senior Machine Learning Engineer - Policy & Safety |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York, NY |
| Department | Engineering |
| Team | Experience |
| Employment Type | Permanent |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.lever.co/spotify/9eca14d3-8e0b-46de-8161-704e07f3d9d0 |
| Apply URL | https://jobs.lever.co/spotify/9eca14d3-8e0b-46de-8161-704e07f3d9d0/apply |
| First Seen At | 2026-05-29 07:00:52Z |
| Last Seen At | 2026-06-23 07:56:53Z |
| Last Checked At | 2026-06-23 07:56:53Z |
| Last Changed At | 2026-06-23 07:56:53Z |
| Inactive At | — |
| Source Posted At | 2026-05-04 07:58:49Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=lever/board=spotify/date=2026-06-23/2026-06-23T07-56-53-337Z-25fb3c1fb125f8989660dc7f15cd809588d3999d4185827e0e1ccff4ee2d857f.json |
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