Applied Scientist — Content Discovery & Personalization

Prime Video & Amazon MGM Studios; Seattle (WA); On-site; USD 142,800 - 193,200; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC is seeking an Applied Scientist for Prime Video Title Lifecycle Presentation. You will build sophisticated machine learning systems for content presentation and discovery, leveraging multi-modal data across text, images, and video to improve ranking and recommendations.

You will work with cutting-edge tools to translate business needs into rapid proofs of concept, collaborating with cross-functional teams to deliver measurable improvements in user engagement and content

Qualifications

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

Responsibilities

• Build large-scale ML systems for content presentation and discovery.
• Analyze terabytes of text and video data to solve real-world problems.
• Translate business requirements into prototypes.
• Invent and implement state-of-the-art solutions.
• Collaborate with teams across content and infrastructure.

Skills

Java

C++

Python

Machine Learning

Deep Learning

Reinforcement Learning

Recommendation Systems

Data Mining

Big Data

Distributed Computing

Education

PhD or MS in CS/CE/ML

Tools

Unix/Linux

TensorFlow/PyTorch

Spark

Job description

Amazon.com Services LLC is seeking an Applied Scientist for Prime Video Title Lifecycle Presentation. You will build sophisticated machine learning systems for content presentation and discovery, leveraging multi-modal data across text, images, and video to improve ranking and recommendations.

You will work with cutting-edge tools to translate business needs into rapid proofs of concept, collaborating with cross-functional teams to deliver measurable improvements in user engagement and content