Senior Applied Scientist — Personalization & Discovery

Prime Video & Amazon MGM Studios; Sunnyvale (CA); On-site; USD 192,200 - 260,000; Full time

Job summary

Prime Video is seeking a hands-on Applied Scientist in Sunnyvale, CA to lead machine learning efforts that power personalized recommendations and video understanding.

You will own end-to-end ML solutions, collaborate with engineers and product managers, and contribute to research published in top venues. This role offers opportunities to influence product strategy and work on cutting-edge foundation-model–driven personalization at scale.

Qualifications

• PhD, or Master’s degree and 6+ years of applied research experience.
• 5+ years of building machine learning models for business application experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Develop AI solutions for Prime Video Recommendation and Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods.
• Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end.
• Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses.
• Effectively communicate technical and non-technical ideas with teammates and stakeholders.
• Stay up-to-date with advancements and the latest modeling techniques in the field.
• Publish your research findings in top conferences and journals.

Skills

Java

C++

Python

Deep learning

Machine learning

Education

PhD or Master's degree

Tools

Spark MLLib

MxNet

TensorFlow

scikit-learn

R

Job description

Prime Video is seeking a hands-on Applied Scientist in Sunnyvale, CA to lead machine learning efforts that power personalized recommendations and video understanding.

You will own end-to-end ML solutions, collaborate with engineers and product managers, and contribute to research published in top venues. This role offers opportunities to influence product strategy and work on cutting-edge foundation-model–driven personalization at scale.