Job ID : 2728533 Amazon.com Services LLC
This is a unique opportunity to build technology and science that millions of people will use every day. Are you excited about working on large scale Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL)?
Check you match the skill requirements for this role, as well as associated experience, then apply with your CV below.
We are embarking on a multi-year journey to improve the shopping experience for customers globally. Amazon Search team creates customer-focused search solutions and technologies that make shopping delightful and effortless for our customers.
Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products.
As Amazon expands to new geographies, we are faced with the unique challenge of maintaining the bar on Search Quality due to the diversity in user preferences, multilingual search and data scarcity in new locales.
We are looking for an applied researcher to work on improving search on Amazon using NLP, ML, and DL technology. As an Applied Scientist, you will lead our efforts in query understanding, semantic matching (e.
g. is a drone the same as quadcopter?), relevance ranking (what is a "funny halloween costume"?), language identification (did the customer just switch to their mother tongue?
machine translation (猫の餌を注文する). This is a highly visible role with a huge impact on Amazon customers and business. As part of this role, you will develop high precision, high recall, and low latency solutions for search.
Your solutions should work for all languages that Amazon supports and will be used in all Amazon locales world-wide. You will develop scalable science and engineering solutions that work successfully in production.
You will work with leaders to develop a strategic vision and long term plans to improve search globally.
We are growing our collaborative group of engineers and applied scientists by expanding into new areas. This is a position on Global Search Quality team in Seattle Washington / Palo Alto California.
We are moving fast to change the way Amazon search works. Together with a multi-disciplinary team you will work on building solutions with NLP / ML / DL at its core.
Along the way, you’ll learn a ton, have fun and make a positive impact on millions of people. Come and join us as we invent new ways to delight Amazon customers.
Key job responsibilities
Design, develop and run online experiments using new and advanced modeling techniques to improve accuracy of semantic matching and therefore relevance of results, for customers worldwide.
Train other scientists and engineers to do the same.
- Drive learnings from online experiments, disseminate knowledge widely.
- Author scientific documentation on the new techniques that are pioneered, to support knowledge dissemination both internally and externally.
- Develop new hypothesis and experimentation ideas that bring step change improvement to semantic matching. Mentor and guide other scientists and engineerings on related research and development.
- Own modules / areas and own collaboration and communication with key partners for those areas.
- Train new hires in model building and experimental methodologies.
About the team
The Global Search Quality (GSQ) team is part of Amazon’s Search organization, responsible for enhancing the shopping experience worldwide by improving search relevance and quality.
Our mission is to make it easy for customers to find relevant products by accurately understanding their search intentions and surfacing the most relevant results, showcasing Amazon’s vast selection.
We focus on developing cutting-edge models, systems, and algorithms that interpret complex natural language queries, reduce irrelevant and increase the number of semantically matched products returned.
Our work encompasses techniques like bi-encoder semantic matching, leveraging diverse data sources, driving continuous improvement, and improving infrastructure and processes.
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with modeling tools such as PyTorch, R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
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