Description
The Personalization team at Spotify makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening.
Our team's goal is to provide users with personalized music and content recommendations. We are looking for a Machine Learning Engineer to join our team and help build the future of music, podcast and audiobook listening experiences for millions of listeners at Spotify.
As a Machine Learning Engineer on our team, you will be responsible for developing and deploying machine learning models to improve the accuracy and relevance of our recommendations. You will work closely with our data scientists, product managers, and engineers to design, implement, and evaluate new features and algorithms.
Responsibilities:
- Utilize in-house and 3rd party Large Language Models (LLMs) to solve language understanding problems
- Employ techniques such as fine-tuning and Retrieval-Augmented Generation (RAG) to improve models
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
- Help drive optimization, testing, and tooling to improve quality of our content enrichment assets
- Collaborate with cross-functional teams of MLEs, data and backend engineers, and other stakeholders including tech research, data science, and product to develop new features and technologies
- Perform data analysis to establish baselines and inform product decisions
- Stay up-to-date on the latest machine learning algorithms and techniques
Requirements:
- Strong background in machine learning, especially experience with Large Language Models
- Professional experience in applied machine learning
- Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, with Python experience required) and cloud platforms (GCP or AWS)
- Hands-on experience implementing or prototyping machine learning systems at scale
- Experience architecting data pipelines and self-sufficiency in getting the data needed to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark
- Agile software processes, data-driven development, reliability, and disciplined experimentation
- Experience and passion for fostering collaborative teams
- Experience with PyTorch, TensorFlow, and/or other scalable Machine learning frameworks. Experience with Ray or TFX is a plus
Where You'll Be:
We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location. This team operates within the Eastern Standard time zone for collaboration.
Additional Information:
The United States base range for this position is $120,465-$172,093 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.