Amazon.com Services LLC
Senior Applied Scientist, Amazon Advertising - Sponsored Products & Brands
Amazon.com Services LLC, Seattle, Washington, us, 98127
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
Amazon is investing heavily in building a world class advertising business, responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses, driving long term growth. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground to create world-class products.
This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize leading-edge engineering and science technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational, multi-turn interfaces.
We are seeking a science leader for our team within Sponsored Products & Brands organization. You'll be working with talented scientists, engineers, and technical program managers to innovate on behalf of our customers. An ideal candidate is able to navigate through ambiguous requirements, working with various partner teams and SDEs, and has experience in Natural Language Processing, Ads recommendation systems, information/evidence retrieval and/or LLM prompt engineering.
Key job responsibilities:
Serve as the Science lead in defining the Science charter for the team (for an entirely new space using LLMs) & leading other AS on the team
Build POCs, experiment, optimize and deploy models into production
Partner with other Science teams within the org to deliver features for a net new shopper experience
Run experiments/weblabs and perform statistical analysis
Mentor other scientists on the team
Partnering with Principal PMT and SDM to influence the Product strategy
Nice to have:
Experience in Ads recommendations & information/evidence retrieval
Experience working with Large Language Models & Prompt Engineering
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
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PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
Amazon is investing heavily in building a world class advertising business, responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses, driving long term growth. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground to create world-class products.
This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize leading-edge engineering and science technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational, multi-turn interfaces.
We are seeking a science leader for our team within Sponsored Products & Brands organization. You'll be working with talented scientists, engineers, and technical program managers to innovate on behalf of our customers. An ideal candidate is able to navigate through ambiguous requirements, working with various partner teams and SDEs, and has experience in Natural Language Processing, Ads recommendation systems, information/evidence retrieval and/or LLM prompt engineering.
Key job responsibilities:
Serve as the Science lead in defining the Science charter for the team (for an entirely new space using LLMs) & leading other AS on the team
Build POCs, experiment, optimize and deploy models into production
Partner with other Science teams within the org to deliver features for a net new shopper experience
Run experiments/weblabs and perform statistical analysis
Mentor other scientists on the team
Partnering with Principal PMT and SDM to influence the Product strategy
Nice to have:
Experience in Ads recommendations & information/evidence retrieval
Experience working with Large Language Models & Prompt Engineering
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
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