美帝的表态# Stock
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大家好。
HR给了我几个组选。有点疑惑，请大家给点意见。有没有组非常好，或者非常坑不要去
的。谢谢。
eCFT
eCommerce Foundational Technologies (eCFT) strives to fulfill this
aspiration by building key services that empower Amazon Retail Business
teams to rapidly develop business ideas into running, "at-scale" software
with minimal developer effort and time.
With inventory located in fulfillment centers around the world, a catalog of
products numbering in the millions, and customers across the globe, we
generate petabytes of data which helps us manage our business. Amazon’s Big
Data Technologies Team (a part of eCFT) allows our business leaders to
leverage catalog, inventory, transaction, clickstream and marketing data to
identify opportunities, support product development and optimize business
decision-making, ultimately resulting in great experiences for customers.
Amazon's Analytical Engine is powered by a heterogeneous array of storage
solutions including super-sized database clusters and non-relational data
stores. As part of the Data Management and Optimization Team, you will be at
the core of building complex software and distributed systems to tackle
some of Big Data Technologies hardest optimization challenges! Come help us
take on this challenge, create a large market impact and drive industry
change by helping define what can be done with Big Data!
We are looking for highly effective software developers that can quickly
design and deliver systems while maintaining a constant customer focus.
Developers on this team are responsible for everything from designing and
building extremely stable components and cutting-edge features to
formulating strategy for data management across all of Amazon's business.
You will mentor other engineers, and work closely with customers to ensure
quality and deliver the best results.
Voice and Nui Shopping (VANS)
Voice and Nui Shopping (VANS) is a new and highly technical org that is
building Shopping 2.0 for Amazon. This team owns creation of a natural,
personal shopping assistant on any connected device globally. Key problem
spaces include natural language understanding, conversation engine, semantic
search, knowledge graphs, algorithms, ranking problems, and significant
applications of machine learning.
Hardlines
The Hardlines technical teams currently own the end-to-end experience for
multiple stores on Amazon.com in areas such as Consumer Electronics,
Wireless, Automotive, and Industrial & Scientific Supplies. In addition, we
own AmazonSupply.com, which is a dedicated B2B marketplace with core
transactional and product discovery features focused on the needs of our
business customers. Our applications are built using a combination of Object
Oriented, Functional, and Scripting languages like Java, C++, Closure, Ruby
, and Perl. We consume a lot of Amazon Web Services (AWS) like EC2, S3, and
DynamoDB, and a lot of internal services like Authentication, Payments,
Catalog and Search. At the same time we produce web services that are
consumed by our teams and other teams in Amazon. Hardlines uses machine
learning to resolve some of the problems we have around pricing, data
classification and personalization. Interested in Open Source technologies?
Hardlines uses Linux, Apache, Tomcat, Spring, JUnit, jQuery, Mason, and
others; several of our developers have been Open Source contributors.
Selection Classification
Want to teach machines to search for needles in a haystack? Ever wonder how
you can keep the world’s largest selection also the world’s safest and
legally compliant selection? Then come join a team with the charter to
monitor and classify the billions of items in the Amazon catalog to ensure
compliance with various legal regulations and policies. The Selection
Classification team is looking for outstanding Software Development
Engineers to build technology to automatically monitor the billions of
products on the Amazon platform. The software and processes built by this
team are a critical component of building a catalog that our customers trust.
You will have an opportunity to work with cutting edge machine learning
algorithms on large datasets. Your will need to build Amazon scale
applications running on Amazon Cloud that both leverage and create new
technologies to process large volumes of data that derive patterns and
conclusions from the data.
HR给了我几个组选。有点疑惑，请大家给点意见。有没有组非常好，或者非常坑不要去
的。谢谢。
eCFT
eCommerce Foundational Technologies (eCFT) strives to fulfill this
aspiration by building key services that empower Amazon Retail Business
teams to rapidly develop business ideas into running, "at-scale" software
with minimal developer effort and time.
With inventory located in fulfillment centers around the world, a catalog of
products numbering in the millions, and customers across the globe, we
generate petabytes of data which helps us manage our business. Amazon’s Big
Data Technologies Team (a part of eCFT) allows our business leaders to
leverage catalog, inventory, transaction, clickstream and marketing data to
identify opportunities, support product development and optimize business
decision-making, ultimately resulting in great experiences for customers.
Amazon's Analytical Engine is powered by a heterogeneous array of storage
solutions including super-sized database clusters and non-relational data
stores. As part of the Data Management and Optimization Team, you will be at
the core of building complex software and distributed systems to tackle
some of Big Data Technologies hardest optimization challenges! Come help us
take on this challenge, create a large market impact and drive industry
change by helping define what can be done with Big Data!
We are looking for highly effective software developers that can quickly
design and deliver systems while maintaining a constant customer focus.
Developers on this team are responsible for everything from designing and
building extremely stable components and cutting-edge features to
formulating strategy for data management across all of Amazon's business.
You will mentor other engineers, and work closely with customers to ensure
quality and deliver the best results.
Voice and Nui Shopping (VANS)
Voice and Nui Shopping (VANS) is a new and highly technical org that is
building Shopping 2.0 for Amazon. This team owns creation of a natural,
personal shopping assistant on any connected device globally. Key problem
spaces include natural language understanding, conversation engine, semantic
search, knowledge graphs, algorithms, ranking problems, and significant
applications of machine learning.
Hardlines
The Hardlines technical teams currently own the end-to-end experience for
multiple stores on Amazon.com in areas such as Consumer Electronics,
Wireless, Automotive, and Industrial & Scientific Supplies. In addition, we
own AmazonSupply.com, which is a dedicated B2B marketplace with core
transactional and product discovery features focused on the needs of our
business customers. Our applications are built using a combination of Object
Oriented, Functional, and Scripting languages like Java, C++, Closure, Ruby
, and Perl. We consume a lot of Amazon Web Services (AWS) like EC2, S3, and
DynamoDB, and a lot of internal services like Authentication, Payments,
Catalog and Search. At the same time we produce web services that are
consumed by our teams and other teams in Amazon. Hardlines uses machine
learning to resolve some of the problems we have around pricing, data
classification and personalization. Interested in Open Source technologies?
Hardlines uses Linux, Apache, Tomcat, Spring, JUnit, jQuery, Mason, and
others; several of our developers have been Open Source contributors.
Selection Classification
Want to teach machines to search for needles in a haystack? Ever wonder how
you can keep the world’s largest selection also the world’s safest and
legally compliant selection? Then come join a team with the charter to
monitor and classify the billions of items in the Amazon catalog to ensure
compliance with various legal regulations and policies. The Selection
Classification team is looking for outstanding Software Development
Engineers to build technology to automatically monitor the billions of
products on the Amazon platform. The software and processes built by this
team are a critical component of building a catalog that our customers trust.
You will have an opportunity to work with cutting edge machine learning
algorithms on large datasets. Your will need to build Amazon scale
applications running on Amazon Cloud that both leverage and create new
technologies to process large volumes of data that derive patterns and
conclusions from the data.
