Build Spotify’s personalized recommendations remotely with Python and PyTorch expertise. Shape Home feed experiences serving millions of listeners globally. As a Staff Machine Learning Engineer, you will own personalization systems across Spotify Home Surfaces. The work combines recommendation systems, ranking models, large language models, experimentation, and production-scale machine learning infrastructure. You will take models from research into production while guiding technical direction in ambiguous problem spaces. Key Responsibilities:

Own machine learning models powering Spotify’s Home feed Design personalized recommendations for millions of listeners Build content systems for agentic and AI-powered experiences Drive experimentation, monitoring, evaluation, and optimization Improve platforms,



pipelines, and production personalization systems Requirements:

Eight or more years building production machine learning systems Deep expertise in recommendations, ranking, personalization, or discovery Robust Python proficiency and hands-on PyTorch experience Experience training, fine-tuning, evaluating, and optimizing large language models Understanding of large-scale inference latency, reliability, and cost Apply recommendation systems, Python, PyTorch, and machine learning leadership to Spotify’s globally scaled Home experiences remotely.

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📌 Staff Machine Learning Engineer Recommendations (Winnipeg)
🏢 pofft Technology
📍 Winnipeg