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# Lead Machine Learning Engineer

- **Company:** UMG Recordings Services Inc.
- **Location:** Los Angeles, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, BigQuery, Cloud Database, Code Review, Software Debugging, Decision Support Systems, Distributed Systems, Data Flow Control, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Software Engineering, Workflow Management Systems, Large Language Models, Information Technology, Data Lineage, Machine Learning Operations, Software Version Control, Data Pipelines, Human in the Loop
- **Published:** November 9, 2026
- **Apply:** https://www.juju.com/job/28_25197_698b7e141e05051696e7417efdbbae1e

## About the Role

A bachelor's or advanced degree in computer science, engineering, mathematics, or a related field, or equivalent practical experience. Typically 5+ years of experience in software, machine learning, data, or platform engineering with ownership of production systems and ambiguous, high-impact problems. Experience engineering modern AI systems, including LLM-based workflows, retrieval, grounding, structured generation, tool use, safety controls, and human review, with clear evaluation and monitoring practices. Strong Python and software engineering skills, including testing, code review, version control, debugging, maintainable design, and experience with a second production language or equivalent systems experience. Experience with cloud-based data and ML platforms. UMG workloads use GCP and BigQuery; experience with services such as Vertex AI, Dataflow, or Cloud Composer is valuable, while equivalent AWS or cloud-agnostic experience is also relevant. Experience building
and operating data pipelines, distributed systems, APIs, services, workflow orchestration, model serving, batch or online inference, and refresh or retraining processes. Ability to collaborate across technical and business disciplines, communicate tradeoffs clearly, take ownership without formal authority, and choose a simpler reliable solution when it is better than a more complex model. Especially valuable Experience in music, media, entertainment, streaming marketplaces, advertising, or another industry where culture, consumer behavior, and business conditions change rapidly. Experience working with complex non-tabular data, such as audio, text, images, or video. Experience building decision-support products and automated workflows rather than standalone models or static dashboards. Experience establishing model governance, data provenance, copyright safety protocols, or human-in-the-loop review systems. Experience building systems for artist discovery, catalog
understanding, fan marketing, rights management, fraud detection, or trust and safety., We are an E-Verify employer in Alabama, Arizona, Georgia, Mississippi, North Carolina, South Carolina, Tennessee, and Utah. Please note, UMG is not enrolled in E-Verify in California and New York, and cannot support employment of candidates whose employer must enroll in E-Verify, for example candidates on STEM-OPT. For more information, please click on the following links. E-Verify Participation Poster: English / Spanish E-Verify Right to Work Poster: English | Spanish

Job Category: Data, Analytics & Business Intelligence Salary Range: $200k-$250k The actual base salary offered depends on a variety of factors, which may include, as applicable, the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job.

## Description

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 support-choosing a simpler reliable approach whenever is appropriate.