Applied Scientist, Amazon Music - Catalog [musiciq]

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Applied Scientist role at Amazon Music focused on designing and developing end-to-end ML systems for understanding music across sonic, thematic, cultural, and lyrical dimensions. Responsibilities include framing business problems as ML tasks, building/training/evaluating models on large datasets, implementing data pipelines and serving systems, analyzing results, and communicating findings. The role aims to power intelligent music experiences and grow customer engagement.

What you'd actually do

  1. Collaborate with scientists, engineers, and product managers to define and frame business problems as ML or optimization tasks.
  2. Build, train, and evaluate models using large, complex datasets.
  3. Implement scalable data pipelines and model-serving systems.
  4. Analyze experimental results, draw insights, and refine models to improve accuracy and robustness.
  5. Communicate findings and recommendations to technical and non-technical audiences.

Skills

Required

  • building models for business application
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • programming in Java, C++, Python or related language
  • algorithms and data structures
  • parsing
  • numerical optimization
  • data mining
  • parallel and distributed computing
  • high-performance computing

Nice to have

  • Unix/Linux
  • professional software development

What the JD emphasized

  • end-to-end systems
  • technical roadmaps
  • production level projects
  • large, complex datasets
  • scalable data pipelines
  • model-serving systems
  • experimental results
  • accuracy and robustness
  • new algorithms and techniques

Other signals

  • end-to-end systems
  • technical roadmaps
  • production level projects
  • large, complex datasets
  • scalable data pipelines
  • model-serving systems
  • experimental results
  • accuracy and robustness
  • new algorithms and techniques