# Machine Learning Engineering Manager, Personalization

**Company:** [Spotify](https://hotfix.jobs/companies/spotify)
**Location:** Remote
**Role:** Engineering Management
**Experience:** 5+ years
**Skills:** Machine Learning, LLMs, Generative AI, Python, production ml systems, ml lifecycle, Experimentation, software engineering practices
**Posted:** 2026-07-30

> Lead a team of ML, backend, and data engineers focused on ranking and personalizing Spotify experiences like Radio and Daily Mix. Set technical direction for production ML systems and generative recommendations using LLMs while providing people leadership and cross-functional partnership.

## Job Description

## What You'll Do
- Lead, coach, and develop a team of machine learning engineers, creating an inclusive, high-performing engineering culture.
- Set the technical direction for the team while partnering with Product, Data Science, and Engineering leaders to deliver impactful machine learning capabilities.
- Guide the design, development, deployment, and operation of production machine learning systems at scale.
- Support engineers through technical mentorship, career development, performance management, and regular feedback.
- Drive execution by helping the team prioritize work, remove obstacles, and continuously improve delivery.
- Foster engineering excellence through modern software engineering practices, experimentation, and operational excellence.
- Partner across squads and missions to influence technical strategy and ensure alignment across the Personalization organization.
- Champion thoughtful adoption of emerging machine learning technologies, including large language models, where they create meaningful user value.

## Who You Are
- You have experience leading and developing high-performing engineering teams.
- You have built trust through coaching, mentoring, and supporting engineers in their career growth.
- You have deep expertise building and operating production machine learning systems at scale.
- You understand the end-to-end machine learning lifecycle, from experimentation through deployment and monitoring.
- You are experienced working with modern machine learning techniques, including large language models and generative AI applications.
- You communicate effectively across engineering, product, and data science partners.
- You care about building inclusive teams where collaboration, curiosity, and continuous learning thrive.
- You balance technical excellence with pragmatic decision-making and delivering meaningful business outcomes.

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**Apply:** https://hotfix.jobs/jobs/7510172c-607d-461d-a73c-2cd05ab4c923
**Canonical:** https://hotfix.jobs/jobs/7510172c-607d-461d-a73c-2cd05ab4c923