Staff Machine Learning Engineer, Home Surfaces
Spotify· Engineering – Personalization
Hybrid (New York, NY / Boston, MA)$227.5k - $325kPermanentPosted 4d ago
About the role
The Personalization team builds recommendations to improve what listeners play next. The Surfaces Podcasts team handles podcast recommendations across Home and Now Playing, focusing on scalable personalized discovery and engagement. This role shapes the future of personalized discovery at Spotify, bridging recommendation systems, large language models, and production ML infrastructure.
Responsibilities
- Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience.
- Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally.
- Build content recommendation systems for emerging agentic and AI-powered user experiences.
- Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches.
- Partner closely with Product Managers, Engineers, Data Scientists, and Designers to define and execute experimentation strategies.
- Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency.
- Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale.
- Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of our personalization systems.
- Mentor and support other Machine Learning Engineers, sharing knowledge and helping strengthen engineering practices across the team.
Qualifications
- Deep experience building and deploying machine learning systems in production environments.
- Deep experience with recommendation systems, ranking models, personalization, or large-scale content discovery platforms.
- Proficient in Python and hands-on experience building ML systems with PyTorch.
- Experience with large language model training, fine-tuning, evaluation, and optimization techniques, including SFT, distillation, and LoRA.
- Experience with large-scale inference systems and understanding latency, reliability, and cost optimization challenges.
- Commitment to high-quality user experiences through thoughtful applications of machine learning.
- Effective communication with technical and non-technical partners and ability to influence technical decisions beyond the immediate team.
- Ability to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
- Experience operating distributed ML workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.
- Experience building and maintaining data pipelines and orchestration workflows using Flyte, Airflow, BigQuery, and cloud-based storage platforms.
Skills
Required:Machine learning system design and production deploymentRecommendation systems / ranking modelsPythonPyTorchLarge language model training / fine-tuningDistributed ML workloadsData pipelines and orchestration
Benefits
- health insurance
- six month paid parental leave
- 401(k) retirement plan
- monthly meal allowance
- 23 paid days off
- 13 paid flexible holidays
- paid sick leave
Last updated Oct 21, 2026. Interested? Apply on the company site.
About Spotify
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Spotify is a digital music service that gives you access to millions of songs.
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