About the role

Machine Learning/AI Engineer at Warner Music Group developing AI applications for music consumption insights. Collaborating with tech leadership and data scientists for scalable solutions.

Responsibilities

Develop a strong understanding of the business problems we are trying to solve.
Partner with tech leadership and data scientists to identify business problems amenable to machine learning solutions. Own the entire AI application lifecycle from model definition and data preparation to deployment, monitoring, and maintenance.
Design, implement, and launch systems that enable scalable AI applications, including robust data pipelines, feature stores, and high-throughput model serving APIs.
Ensure that we are able to run modeling experiments and launches with maximal efficiency, quality, reliability, and repeatability in a large-scale environment with > 2TB of incoming data per day and a total corpus in excess of 20PB.
Establish and maintain MLOps practices to automate and streamline the entire AI development lifecycle, including experiment tracking, model registries, and automated retraining and deployment.
Mentor more junior MLEs and Data Scientists.
Work closely with cross-functional partners to define project objectives and deliverables.

3+ years of full-time hands-on experience building scaled ML systems, training large ML models, or equivalent experience.
1+ year of AI engineering experience.
Bachelor’s Degree or above in a quantitative field.
Excellent coding and system design skills.
Strong practical ML knowledge, working knowledge of ML theory, and a deep understanding of the AI application stack and lifecycle in the context of foundation models, from evaluation to deployment.
Demonstrated experience making an impact with foundation models, including the application of techniques like prompt engineering and retrieval-augmented generation (RAG).
High sense of ownership and a drive to deliver impact in a fast-paced, evolving, ambiguous environment.
Ability to collaborate closely with Data Scientists, Software Engineers, and Product Managers.
Strong communication skills and ability to influence roadmaps and ML/AI strategy.
Experience with cloud computing services or platforms (preferably AWS).
Experience with both Snowflake and Databricks is a plus.