# Machine Learning Engineering Manager - Personalization
**Company:** [Spotify](https://hotfix.jobs/companies/spotify)
**Location:** Remote
**Skills:** Machine Learning, Generative AI, LLMs, Backend Services, Model Evaluation, Kubernetes, Python, TensorFlow, PyTorch, Scalable Systems
**Posted:** 2026-04-24
> Leads engineering team building ML systems for safe personalization recommendations, search, and AI experiences at Spotify. Requires production ML deployment experience, generative AI, scalable backends, and cross-team collaboration.
## Job Description
## What You'll Do

- Design, build, and improve machine learning systems that power safety across personalization surfaces such as recommendations, search, and emerging AI experiences
- Contribute to the platformization of safety systems, enabling scalable and reusable solutions across teams
- Develop and operate high-throughput, low-latency backend services powered by ML models
- Partner with Product, Trust & Safety, and Content Platform to translate safety needs into practical technical solutions
- Work on both traditional ML models and generative AI systems, including integrating third-party and in-house foundational models
- Contribute to evaluation frameworks, including labeling strategies, ground truth creation, and model validation approaches
- Collaborate with foundational model teams to embed safety into LLM-based and agent-driven experiences
- Use metrics and experimentation to continuously improve system performance, safety outcomes, and user experience

## Who You Are

- Experienced in building and deploying machine learning systems in production environments
- Hands-on experience with both traditional ML approaches and newer generative AI techniques
- Worked with scalable backend systems that require reliability, low latency, and high availability
- Understand how to apply ML solutions to real-world product challenges, ideally in consumer-facing products
- Experience with model evaluation approaches such as labeling workflows, red-teaming, or ground truth data generation
- Comfortable working across disciplines, collaborating with product managers, researchers, and policy partners
- Care deeply about building safe, responsible, and inclusive user experiences
- Bring a thoughtful, metrics-driven approach to problem solving and decision-making
**Apply:** https://hotfix.jobs/jobs/machine-learning-engineering-manager-personalization-at-spotify-d505fcbd-f310-4333-90c2-09d3daa9eef1
**Canonical:** https://hotfix.jobs/jobs/machine-learning-engineering-manager-personalization-at-spotify-d505fcbd-f310-4333-90c2-09d3daa9eef1