Sales AI Scientist: Generative ML for Advertising

Amazon; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon.com Services LLC is seeking an Applied Scientist to shape Advertising and B2B Sales with AI-first initiatives. You will build production-ready models and collaborate with cross-functional teams to drive new insights for advertisers.

Join a fast-growing team in Seattle, WA, advancing state-of-the-art ML research, scalable deployment, and impactful projects across the ad sales lifecycle, with opportunities to publish and influence product direction.

Qualifications

• 3+ years of building models for business applications.
• PhD, or Master's degree with 4+ years CS/CE/ML or related field.
• Experience with patents or publications in top-tier venues.
• Proficient in Java, C++, Python or related language.
• Background in algorithms, data structures, optimization and large-scale computing.

Responsibilities

• Conceptualize and lead state-of-the-art ML/AI research for ad sales optimization.
• Design and implement models and algorithms with cross-functional teams.
• Run A/B experiments, analyze data and publish findings.
• Improve scalability, efficiency and automation of analytics and deployment.
• Collaborate with software engineers and product managers to drive feature adoption.
• Translate complex results into actionable business guidance for stakeholders.

Skills

Modeling for business applications

Patents or publications

Java / C++ / Python

Cross-functional collaboration

ML / machine learning

Education

PhD or MS+4 years CS/CE/ML

Tools

Java

C++

Python

Job description

Amazon.com Services LLC is seeking an Applied Scientist to shape Advertising and B2B Sales with AI-first initiatives. You will build production-ready models and collaborate with cross-functional teams to drive new insights for advertisers.

Join a fast-growing team in Seattle, WA, advancing state-of-the-art ML research, scalable deployment, and impactful projects across the ad sales lifecycle, with opportunities to publish and influence product direction.