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Spotify
Design, scale, evaluate, and deploy reward signals for recommendations using RL methods and LLMs, lead collaborations to integrate and A/B test these signals, and promote best practices for ML systems development.
Requires a strong background in machine learning, expertise in Reinforcement Learning (especially for recommendations), and proficiency in statistics, optimization, sequential models, transformers, and generative AI.
The Rewards team in Personalization (PZN) is defining the next generation of large-scale personalization at Spotify by pioneering novel Reinforcement Learning (RL) methods for Large Language Models (LLMs). We drive massive impact across all recommendations discovery surfaces by moving beyond simple clicks to model and optimize for true long-term user satisfaction. Our core mission is to bridge discovery with lasting listening habits by developing and deploying sophisticated, mid-term behavioral reward signals—such as retention and habit formation metrics—that directly shape the LLM-powered recommendation experience.
We are looking for a Machine Learning Engineer to make impactful changes to our recommendations and discovery algorithms. As an integral part of the squad, you will collaborate with research scientists, data scientists, and other engineers across PZN in prototyping and productizing state-of-the-art ML at the intersection of recommendations and long-term user satisfaction.
The United States base range for this position is $184,050- $262,928 plus equity. The benefits available for this position include 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. These ranges may be modified in the future.
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Base Salary (from JD)
$184,050 – $262,928
AI Est. Total Comp
$330,307
Location
New York, NY
Work Type
Hybrid
Seniority
senior
Experience
5-8 years
Category
ML Engineering
Visa Sponsorship
Unknown
16 H1B cases filed
Quality Score
6.2