Lead Machine Learning Engineer - Santa Monica, 90404

📌How we LEAD

Universal Music Group is building an Applied AI and Machine Learning function to help our teams discover and develop artists, connect with fans, make stronger commercial decisions, and protect the integrity of the music ecosystem.

We are looking for a Lead Machine Learning Engineer to build, ship, and operate reliable machine learning and AI systems that create durable value across UMG. This is a senior individual-contributor role for an engineer who combines strong software and systems expertise with practical knowledge of the AI and ML lifecycle.

You will turn models, data products, and AI workflows into maintainable production capabilities across revenue forecasting, artist, catalog intelligence and talent scouting, release marketing, and rights and ecosystem integrity. The role focuses on reproducible development, rigorous evaluation, safe deployment, observability, cost efficiency, and continuous improvement.

📌How youll CREATE

Core MLOps & Production Infrastructure

• 🔹Lead initiatives from problem framing and data assessment through deployment, evaluation, monitoring, and sustained adoption (versus reach a well-evidenced decision not to build).
• 🔹Build and operate reliable ML and LLM-powered workflows, including retrieval and grounding, structured outputs, tool and API integrations, orchestration, batch or real-time inference, CI/CD, and safe rollback.
• 🔹Establish AI evaluation and observability using representative and adversarial test sets, regression tests, human review where appropriate, traces, drift detection, latency, quality, safety, usage, and cost metrics.

Data & Feature Engineering

• 🔹Build reliable data and feature pipelines from streaming consumption data, release metadata, social campaign data, catalog information, and commercial finance systems; monitor completeness, freshness, anomalies, and data lineage.
• 🔹Develop and operate models across personalization, recommender systems, search and ranking, time-series forecasting, anomaly detection, and decision supportchoosing a simpler reliable approach whenever is appropriate.

Business Stakeholders

• 🔹Move generative and multimodal AI capabilities from prototypes into dependable, cost-effective workflows that help people make decisions and take action.
• 🔹Partner with ML scientists, data engineers, product managers, designers, domain experts, A&R, Marketing, Finance, and labels; contribut…