Applied Scientist: Scale ML for Prime Video

Amazon; Culver City (CA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon.com Services LLC's Prime Video Science team seeks an Applied Scientist to build ML models on large-scale data to simulate customer behavior and inform content investment decisions.

You will apply reinforcement learning, causal inference, and agentic AI concepts, collaborating with business, finance, engineering, and science teams to prototype and deploy production-ready systems. Strong communication and ability to translate findings into actionable insights are essential.

Qualifications

• 3+ years of building machine learning models or developing algorithms 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

Responsibilities

• Build models that simulate customer behavior to answer counterfactual 'what-if' questions that guide major content and product investment decisions.
• Apply deep learning, reinforcement learning, causal inference, and experimental design to large-scale customer data to model how customers respond to change.
• Design and prototype agentic AI systems and other novel ML approaches and research new methods to improve the accuracy and scale of our models.
• Validate and calibrate models against real-world randomized experiments, and partner with software engineers to deliver scalable, production-ready systems.
• Translate model outputs into clear recommendations and communicate results to business, finance, and science stakeholders through both technical papers and business-facing documents.

Skills

Machine learning models

Reinforcement learning

Causal inference

Algorithms

Education

PhD

MS + 4+ years CS/ML/CE

Tools

Java

C++

Python

Job description

Amazon.com Services LLC's Prime Video Science team seeks an Applied Scientist to build ML models on large-scale data to simulate customer behavior and inform content investment decisions.

You will apply reinforcement learning, causal inference, and agentic AI concepts, collaborating with business, finance, engineering, and science teams to prototype and deploy production-ready systems. Strong communication and ability to translate findings into actionable insights are essential.