Machine Learning Engineer I, Personalization , Minesweeper

Spotify is a leading audio streaming subscription service, and they are seeking a Machine Learning Engineer I to join their Personalization team. The role involves utilizing AI and ML techniques to enhance music, podcast, and audiobook recommendations, while collaborating with cross-functional teams to develop innovative features.

Responsibilities:

• Utilize in-house and 3rd party LLMs to solve language understanding problems
• Employ techniques such as fine-tuning and 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
• Be a participant in our AI Foundation’s ML community and work collaboratively and efficiently within our existing platforms and systems Perform data analysis to establish baselines and inform product decisions
• Stay up-to-date on the latest machine learning algorithms and techniques

Requirements:

• You have a strong background in machine learning, especially experience with Large Language Models
• You have 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)
• You have some hands-on experience implementing or prototyping machine learning systems at scale
• You have experience architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation
• You have 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
• Bonus if you have experience with architecting near real time pipelines