What You'll Do

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

Who You Are

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 are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark
Care about 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
Bonus if you have experience with architecting near real time pipelines