Applied Scientist, Amazon Music

Are you passionate about applying machine learning and data-driven techniques to solve real-world problems at global scale? Amazon is seeking an Applied Scientist who combines curiosity, creativity, and strong analytical skills to build models and algorithms that power customer experiences and business decisions.
As an Applied Scientist I, you will work with senior scientists and engineers to design, train, and deploy ML models using large-scale datasets. You will experiment with modern techniques in supervised and unsupervised learning, natural language processing, computer vision, or optimization—depending on the team’s focus area. You’ll also have opportunities to learn Amazon’s scalable infrastructure, experiment platforms, and science best practices.
This role is ideal for someone early in their career who enjoys working in collaborative, multidisciplinary teams and is excited by the opportunity to learn, innovate, and deliver measurable impact to customers.
Key job responsibilities
Collaborate with scientists, engineers, and product managers to define and frame business problems as ML or optimization tasks.
Build, train, and evaluate models using large, complex datasets.
Implement scalable data pipelines and model-serving systems.
Analyze experimental results, draw insights, and refine models to improve accuracy and robustness.
Communicate findings and recommendations to technical and non-technical audiences.
Continuously learn and apply new algorithms and techniques to improve existing systems.
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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