Staff Machine Learning Engineer, Home Surfaces

Spotify•Boston, MA

49d•$227,495 - $324,993

About The Position

The Personalization team builds Spotify features that help listeners decide what to play next. The Surfaces Podcasts team owns podcast recommendations across prominent Spotify surfaces, including Home and Now Playing, helping listeners discover shows and episodes while connecting creators with audiences. As a Staff Machine Learning Engineer, you will shape personalized discovery and engagement by working across recommendation systems, large language models, and production-scale machine learning infrastructure. You will take models from research to production, set technical direction in ambiguous problem spaces, and address personalization challenges at global scale. The role focuses on improving Home feed recommendations, including Shortcuts, and building recommendations for emerging agentic and AI-powered experiences.

Requirements

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.
Proficiency in Python and hands-on experience building machine learning 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 of latency, reliability, and cost optimization challenges.
Ability to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
Experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.
Experience building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.
Effective communication with technical and non-technical partners and ability to influence technical decisions beyond the immediate team.
Care for creating high-quality user experiences through thoughtful applications of machine learning.

Responsibilities

Own and improve machine learning models and systems powering the Home feed, including the Shortcuts experience.
Design, build, and ship personalized recommendations for 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 approaches such as supervised fine-tuning, distillation, and parameter-efficient training.
Partner 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 machine learning platform capabilities, data pipelines, and production systems supporting personalization at Spotify scale.
Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of personalization systems.
Mentor and support other Machine Learning Engineers, share knowledge, and strengthen engineering practices across the team.