Senior Applied Scientist, Personalization & Discovery

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

Benefits offered by this job

RSUs

Health insurance

401(k) matching

Job summary

Amazon Science in Sunnyvale, CA, seeks a machine learning scientist to advance foundation models for content understanding and multimodal learning across Prime Video surfaces. You will own end-to-end research-to-production solutions and collaborate with engineers and product managers.

The role emphasizes hands-on ML, opportunities to publish findings, and leadership in research while helping personalize recommendations to improve viewing experiences for customers.

Qualifications

• PhD or Master's degree in CS, CE, ML or related field with 4+ years of relevant experience.
• Strong programming skills in Java, C++, Python.
• Experience with algorithms, data structures, data mining, and parallel computing.

Responsibilities

• Develop foundation models for content understanding using deep learning and multimodal learning.
• Build time-series models to understand customer behavior and viewing trajectories.
• Collaborate with engineers and product managers to deploy end-to-end solutions.
• Design offline and online experiments to evaluate proposals using data analyses.
• Communicate complex ideas clearly to teammates and stakeholders.
• Stay updated on state-of-the-art modeling techniques and publish findings.

Skills

3+ years experience

Java

C++

Python

Algorithms & data structures

Distributed computing

Education

PhD or Master's in CS/CE/ML or related field

Tools

Unix/Linux

Job description

Amazon Science in Sunnyvale, CA, seeks a machine learning scientist to advance foundation models for content understanding and multimodal learning across Prime Video surfaces. You will own end-to-end research-to-production solutions and collaborate with engineers and product managers.

The role emphasizes hands-on ML, opportunities to publish findings, and leadership in research while helping personalize recommendations to improve viewing experiences for customers.