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Description:
The Personalization (PZN) team at Spotify aims to enhance the listening experience by providing tailored recommendations for music, podcasts, and audiobooks.
The role involves designing, building, evaluating, and shipping machine learning (ML) solutions for Spotify’s personalization products.
Collaboration with cross-functional teams, including user research, design, data science, product management, and engineering, is essential to develop new product features that connect artists and fans.
Responsibilities include prototyping new approaches and scaling production solutions for hundreds of millions of active users.
The position promotes best practices in ML systems development, testing, and evaluation within the team and the organization.
The candidate will join an active group of machine learning practitioners.
Requirements:
The ideal candidate is an experienced ML practitioner eager to tackle complex real-world problems in a fast-paced, collaborative environment.
A strong background in machine learning, natural language processing, and generative AI is required, with practical experience in developing real-world applications.
Hands-on expertise in implementing end-to-end production ML systems at scale using Python, Java, or Scala is necessary.
Experience with Pytorch and/or TensorFlow is considered a strong plus.
The candidate should have experience designing end-to-end tech specifications and modular architectures for ML frameworks in collaboration with product teams.
Familiarity with large-scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms such as GCP or AWS is required.
Benefits:
The position offers a competitive salary range of $138,250 to $197,500, plus equity.
Benefits include health insurance, a six-month paid parental leave, and a 401(k) retirement plan.
Employees receive a monthly meal allowance, 23 paid days off, and 13 paid flexible holidays.
Paid sick leave is also provided.
Spotify is committed to inclusivity and offers reasonable accommodations during the recruitment process to support all candidates.
Apply now
Please, let Spotify know you found this job
on RemoteYeah
.
This helps us grow 🌱.