Senior Applied Scientist: Generative AI for Ads

Amazon; Boulder (CO); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon Ads is seeking an Applied Scientist to advance ML across the full advertising lifecycle, from ranking and personalization to creative optimization and measurement. You’ll work on generative AI and large language models at scale, balancing customer needs with advertiser goals while collaborating with engineers, product managers, and other scientists.

The role offers access to extensive data and computational resources, fostering innovation and technical leadership with real-world impact on

Qualifications

• 5+ years building machine learning models for business applications.
• PhD or Master’s plus 6+ years of applied research experience.
• Proficient in Java, C++, Python or related languages.
• Experience with neural deep learning methods and ML workflows.

Responsibilities

• Research and implement cutting-edge ML approaches, incl. generative AI and LLMs.
• Develop and deploy ML solutions across ranking, personalization, NLP, CV, recommender systems.
• Lead end-to-end projects with large data scale and multidisciplinary teams.
• Balance stakeholder needs to optimize ad customer relevance and advertiser goals.
• Build and validate models, run experiments, and deploy to production with cross-functional teams.
• Design A/B experiments to measure business impact and insights.

Skills

ML model development

Programming: Java/C++/Python

Deep learning

Education

PhD

Master’s degree

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Job description

Amazon Ads is seeking an Applied Scientist to advance ML across the full advertising lifecycle, from ranking and personalization to creative optimization and measurement. You’ll work on generative AI and large language models at scale, balancing customer needs with advertiser goals while collaborating with engineers, product managers, and other scientists.

The role offers access to extensive data and computational resources, fostering innovation and technical leadership with real-world impact on