Machine Learning Engineer, Amazon Music Catalog Quality
Department:
Job Summary
Our mission is to provide high-quality dynamically validated and enriched catalog metadata with low latencies across the Amazon Music experience. We automate the detection and correction of metadata anomalies including misattributed tracks duplicate content incorrect artist information and incomplete album details while providing internal teams with the tools and flexibility to continuously improve catalog integrity at scale.
Key job responsibilities
- Design build and operate scalable machine learning pipelines and online serving systems
- Work closely with applied scientists to optimize ML model performance and implement end-to-end solutions from experimentation through production
- Drive technology choices and continuous innovation for ML infrastructure across the sponsored products organization
- Collaborate with product managers scientists and engineers to deliver the right product for customers
- Build and maintain strong relationships across partner disciplines (Product Science and Engg) to ensure customer-focused delivery
- Contribute to operational excellence - monitoring troubleshooting and supporting high-volume low-latency systems
- 3 years of non-internship professional software development experience
- 2 years of non-internship design or architecture (design patterns reliability and scaling) of new and existing systems experience
- Experience working with PyTorch or JAX software
- 2 years of building large-scale machine-learning infrastructure for online recommendation ads ranking personalization or search experience
- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Masters degree in computer science or equivalent
- Knowledge of Machine Learning and LLM fundamentals including transformer architecture training/inference lifecycles and optimization techniques
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Required Experience:
IC
About Company
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