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Machine Learning Engineer, Amazon Music - Catalog Quality

Teknik, data och digitalt · Data, AI och analys · Maskininlärning · Data engineering · Mjukvaruutveckling

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I korthet

Amazon Music is seeking a Machine Learning Engineer to enhance music metadata accuracy and richness using LLMs, computer vision, and deep learning. This role involves designing, building, and operating ML pipelines and collaborating with cross-functional teams to deliver high-quality catalog data at scale.

Ansvarsområden

  • Design, build, and operate scalable machine learning pipelines and online serving systems.
  • Optimize ML model performance and implement end-to-end solutions from experimentation through production.
  • Drive technology choices and continuous innovation for ML infrastructure.
  • Collaborate with product managers, scientists, and engineers to deliver the right product.
  • Build and maintain strong relationships across partner disciplines.
  • Contribute to operational excellence - monitoring, troubleshooting, and supporting high-volume, low-latency systems.

Krav

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture experience (design patterns, reliability and scaling of new and existing systems).
  • 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.

Önskade kvalifikationer

  • 3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Master's degree in computer science or equivalent.
  • Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques.
#Machine Learning#Amazon Music#Catalog Quality
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Företag

Amazon

Publicerade jobb

för 1 månad sedan

Anställningstyp

Heltid

Arbetsform

På plats

Erfarenhetsnivå

Mellannivå

Platser

Bengaluru, India

Kvalifikation

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