Applied Scientist III, Sponsored Products, Amazon Job at Amazon in Santa Clara
Amazon, Santa Clara, CA, United States, 95053
Applied Scientist III, Sponsored Products, Amazon
Job ID: 2846153 | Amazon.com Services LLC
Job Summary
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth.
We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day. We optimize product placements using a combination of machine learning and natural language processing (NLP) algorithms operating in low latency, high-volume systems. We are highly motivated, collaborative and fun-loving, with entrepreneurial drive and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
As an Applied Scientist III, you will take ownership of the technical roadmap and delivery of real-time, scalable machine learning models influencing ad selection, relevance and ranking models. You will work with other Applied Scientists and Machine Learning Engineers to experiment and innovate quickly with a diverse set of models, features and techniques in a high-volume, low-latency environment. Our workflows scan billions of documents, with milliseconds of latency budget while ensuring high relevance of retrieved items. So the level of quality and reliability is critically important.
Responsibilities
- Build machine learning models that can scale to our run-time requirements.
- Run A/B experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new and innovative machine learning approaches.
- Help recruit and mentor other Applied Scientists on the team.
About the Team
The Sponsored Product search entity sourcing delivery team helps deliver billions of ad impressions and millions of daily clicks. Our core charter revolves around building state-of-art machine-learning (ML) and natural-language-processing (NLP) methodologies to improve the search indexing & ranking mechanisms, which will directly improve the customer experience. We’re a talented team of scientists and engineers working on complex and ambiguous problems, and we have an engineering-driven culture that influences business outcomes.
BASIC QUALIFICATIONS
- 6+ 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
PREFERRED QUALIFICATIONS
- Experience in building machine learning models for business application
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
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