Senior Applied Scientist, Personalization & Discovery

Amazon; Sunnyvale (CA); On-site; USD 172,000 - 222,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Job summary

Amazon is seeking an Applied Scientist II for Prime Video Personalization and Discovery Science in Sunnyvale, CA. You will develop ML models for recommendations and search, collaborating with scientists, engineers, and product managers to generate actionable insights and experiments.

You will stay current with state-of-the-art modeling techniques, publish findings at conferences, and contribute to scalable personalization solutions in a fast-paced environment.

Qualifications

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

Responsibilities

• Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods
• Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create experiments to plan roadmaps
• Stay up-to-date with advancements and the latest modeling techniques in the field
• Publish your research findings in top conferences and journals

Skills

ML modeling

Programming in Java/C++/Python

Algorithms & data structures

Education

PhD or Master’s degree with 4+ years in CS/ML or related field

Job description

Amazon is seeking an Applied Scientist II for Prime Video Personalization and Discovery Science in Sunnyvale, CA. You will develop ML models for recommendations and search, collaborating with scientists, engineers, and product managers to generate actionable insights and experiments.

You will stay current with state-of-the-art modeling techniques, publish findings at conferences, and contribute to scalable personalization solutions in a fast-paced environment.