Senior ML Scientist — Ads Response Prediction & GenAI

Amazon; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

RSUs / stock options

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Ads is seeking a Machine Learning Applied Scientist to drive data-informed improvements across Sponsored Products and Brands. You will build scalable ML models, run A/B experiments, and partner with engineers to deploy end-to-end solutions. The role emphasizes GenAI research to optimize ad serving, targeting, and performance insights.

Join a team advancing personalized shopping experiences worldwide, balancing innovation with responsible AI practices and scalable systems.

Qualifications

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

Responsibilities

• Conduct deep data analysis to derive insights and identify opportunities.
• Develop scalable ML models and optimization strategies for business problems.
• Run regular A/B experiments, collect data, and perform statistical analysis.
• Collaborate with software engineers to deliver end-to-end solutions to production.
• Improve scalability, efficiency, and automation of large-scale data analytics and model serving.
• Research new ML and GenAI solutions to optimize SPB advertising processes.

Skills

Java

Python

C++

Deep learning

ML modeling

Statistics

Education

PhD

Master's degree

Tools

R

scikit-learn

Spark MLLib

TensorFlow

NumPy

SciPy

Hadoop

Spark

Job description

Amazon Ads is seeking a Machine Learning Applied Scientist to drive data-informed improvements across Sponsored Products and Brands. You will build scalable ML models, run A/B experiments, and partner with engineers to deploy end-to-end solutions. The role emphasizes GenAI research to optimize ad serving, targeting, and performance insights.

Join a team advancing personalized shopping experiences worldwide, balancing innovation with responsible AI practices and scalable systems.