Hybrid Machine Learning Engineer

at Create Music Group

• Job title: Machine Learning Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $160,000 - $200,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, BigQuery, Cloud, Google Cloud Platform, Python, PyTorch, Scikit-Learn
• Location requirements: Hybrid, Los Angeles, United States

About the role

• Machine Learning Engineer creating and maintaining ML models for intelligent automation and forecasting at Create Music Group. Collaborating with multiple teams to implement AI-driven solutions.

Responsibilities

• Applied Machine Learning Build and maintain ML models for forecasting, anomaly detection, classification, ranking, and optimization across music industry use cases (catalog valuation, royalty reasoning, A&R intelligence, marketing performance, etc.)
• Partner with Analytics & BI to identify, engineer, and validate features that drive meaningful predictive power
• Own the full ML lifecycle — from problem framing and data exploration through training, evaluation, deployment, and monitoring
• Deploy and monitor models in production using modern MLOps tooling
• Instrument models for performance tracking, drift detection, and continuous improvement
• Implement CI/CD, automated testing, model versioning, and observability for all ML systems
• Collaborate with Data Engineering to ensure data quality, feature delivery, and pipeline reliability
• Develop and maintain modular AI agents that automate multi-step workflows across CreateOS (contracts, accounting, distribution, metadata)
• Build and iterate on RAG pipelines, retrieval architectures, and semantic search systems grounded in structured business data
• Implement guardrails, evaluation frameworks, and safe action boundaries for agentic systems
• Translate business problems from non-technical stakeholders into well-scoped ML solutions
• Document model design decisions, evaluation results, and known limitations clearly
• Contribute to a culture of engineering rigor and responsible AI development

Requirements

• 4+ years of software engineering experience in a production environment, with exposure to ML or data science work (academic, professional, or project-based); OR 2+ years of experience specifically as an ML Engineer or Applied Data Scientist
• Strong proficiency in Python and ML frameworks (PyTorch, scikit-learn, XGBoost, or similar)
• Hands-on experience building, deploying, and monitoring models in cloud environments — GCP strongly preferred (AWS or Azure acceptable); familiarity with services such as Vertex AI, BigQuery, Cloud Functions, and Cloud Run is a strong plus
• Solid understanding of modern ML techniques — supervised/unsupervised learning, time series forecasting, embeddings, ranking — and their mathematical foundations
• Experience with LLMs and prompt engineering, including building RAG systems or LLM-powered features
• Comfortable working with structured and unstructured data at scale
• Strong communication skills with the ability to explain complex model behavior to non-technical audiences.