Research

eBay R&D Center Internship opportunity

Are you a passionate Ph.D. student with a strong background in machine learning and data science? Are you experienced in deep learning and eager to apply your skills in a real-world production environment? Look no further!  eBay R&D center in Israel is currently seeking talented interns to join our team for a summer internship.

About eBay R&D center in Israel

eBay is a leading e-commerce  company at the forefront of innovation in machine learning and data science. In the R&D center in Israel we specialize in tackling complex problems related to search, recommendation, ontologies, in big data,  developing cutting-edge solutions that have a real impact on many users across the globe. Our team is composed of industry experts, researchers, and engineers who are dedicated to pushing the boundaries of what’s possible.

Internship Opportunity

As an intern at eBay R&D Center in Israel , you will have the unique opportunity to work with real data, dive into a live production environment, and tackle challenging and interesting problems. You will collaborate closely with our team of experts, who will provide guidance and mentorship throughout your internship journey. This is a hands-on experience that will allow you to apply your theoretical knowledge to practical scenarios, gaining invaluable skills and insights along the way.

Requirements

  • Currently pursuing a Ph.D.|(or have graduated )  in a relevant field (e.g., computer science, machine learning, data science, and related fields), 
  • Strong background and expertise in machine learning and data science
  • Experience with deep learning frameworks and algorithms
  • Proficiency in programming languages especially Python
  • Excellent problem-solving skills and ability to think critically
  • Strong communication and teamwork abilities
  • Writing abilities

 

Benefits:

  • Gain practical experience in a real-world production environment
  • Work on challenging problems with real data and industry experts
  • Receive guidance and mentorship from experienced professionals
  • Expand your knowledge and skills in machine learning and data science
  • Build a valuable network of industry connections

 

Internship Details:

This internship requires you to come to our site once or twice a week to collaborate with our team and work on projects. This in-person interaction will allow you to fully immerse yourself in our dynamic work environment and make the most of the mentorship and guidance provided.

How to Apply:

If you are excited about the prospect of working on cutting-edge projects, alongside industry experts, and have the drive to make a real impact, we would love to hear from you. Please submit your resume, a brief description of your research interests, and any relevant projects or publications to bshapira@ebay.com. Please include “Internship Application – [Your Name]” in the subject line.

Join us at  and take your skills in machine learning and data science to new heights. Together, we can revolutionize the world of technology!

An Image is Worth a Thousand Terms? Analysis of Visual E-Commerce Search
Arnon Dagan, Ido Guy, Slava
Novgorodov
SIGIR 2021 – July 2021, Montreal, Canada
PreSizE: Predicting Size in E-Commerce using TransformersA
Yotam Eshel, Or Levi, Haggai
Roitman, alexander Nus
SIGIR 2021 – July 2021, Montreal, Canada
Automatic Form Filling with Form-Bert
 
Gilad Fuchs, Haggai Roitman, Matan Mandelbrod: 
SIGIR 2021 – July 2021, Montreal, Canada, 2021
Improving Constrained Search Results By Data Melioration 
Ido Guy, Tova Milo, Slava 
Novgorodov, Brit Youngmann
ICDE’ 21 April 2021 , Chania,
Greece
ConCaT: Construction of Category Trees from Search Queries in ECommerce
 
Uri Avron, Shay Gershtein, Ido Guy, Tova Milo, Slava Novgorodov

ICDE’ 21 April 2021 , Chania, Greece

Category Recognition in E-Commerce using Sequence-to-Sequence Hierarchical Classification 
Idan Hasson, Slava Novgorodov, Gilad Fuchs, Yoni Acriche
WSDM’21 – March 2021, Jerusalem, Israel
Generating Tips from Product Reviews
 
Sharon Hirsch, Slava Novgorodov, Ido Guy, Alexander Nus
WSDM’21 – March 2021, Jerusalem, Israel
Event-driven Query      Expansion 
 
 
Guy Rosin, Ido Guy, Kira 
Radinsky
WSDM’21 – March 2021, Jerusalem, Israel
Descriptions from the Customers: Comparative Analysis of Review-based Product Description Generation Methods
Slava Novgorodov, Ido Guy, Guy Elad, Kira Radinsky
ACM Transactions on Internet Technology, Vol. 20, Issue 4, Article 44 (October 2020)
Intent-Driven Similarity in E-Commerce Listings
 
 
 
Gilad Fuchs, Yoni Acriche, Idan Hass  on, Pavel Petrov
CIKM’20 – October 2020, Galway, Ireland
 
E-Commerce Dispute Resolution Prediction
 
 
David Tsurel, Michael Doron, Alexander Nus, Arnon Dagan, Ido Guy, Dafna Shahaf
CIKM’20 – October 2020, Galway, Ireland
 
tdGraphEmbed: Temporal Dynamic Graph-Level Embedding
 
Moran Beladev, Lior Rokach, Gilad Katz, Ido Guy, Kira Radinsky
CIKM’20 – October 2020, Galway, Ireland
 
 
CONCIERGE: Improving Constrained Search Results by Data Melioration
Ido Guy, Tova Milo, Slava Novgorodov, Brit Youngmann

VLDB’20 – August 2020, Tokyo, Japan

Product Bundle Identification using Semi-Supervised Learning
Hen Tzaban, Ido Guy, Asnat Greenstein-Messica, Arnon Dagan, Lior Rokach, Bracha Shapira
SIGIR’20 – July 2020, Xi’an, China
Query Reformulation in E-Commerce Search
 
Sharon Hirsch, Ido Guy, Alexander Nus, Arnon Dagan, Oren Kurland
SIGIR’20 – July 2020, Xi’an, China
MC3: A System for Minimization of Classifier Construction Cost
Shay Gershtein, Tova Milo, Gefen Morami, Slava Novgorodov
SIGMOD’20 – June 2020, Portland, Oregon, USA
 
Minimization of Classifier Construction Cost for Search Queries
 

 

Shay Gershtein, Tova Milo, Gefen Morami, Slava Novgorodov
SIGMOD’20 – June 2020, Portland, Oregon, USA
Inventory Reduction via Maximal Coverage in E-Commerce
 
 
 
Shay Gershtein, Tova Milo, Slava Novgorodov
EDBT’20 – March 2020, Copenhagen, Denmark
Cross-Cultural Transfer Learning for Text Classification 
 
 
 
Dor Ringel, Gal Lavee, Ido Guy, Kira Radinsky
EMNLP’19 – November 2019, Hong Kong, China
Learning to Generate Personalized Product Descriptions
 
 
Guy Elad, Ido Guy, Slava Novgorodov, Benny Kimelfeld, Kira Radinsky
CIKM’19 – November 2019, Beijing, China
ReducE-Comm: Effective Inventory Reduction System for E-Commerce
Shay Gershtein, Tova Milo, Slava Novgorodov
CIKM’19 – November 2019, Beijing, China
Node Embedding over  Temporal Graphs

Uriel Singer, Ido Guy, Kira 
Radinsky
IJCAI’19 – August 2019, Macao, 
China
Generating Product Descriptions from User  Reviews 
Slava Novgorodov, Ido Guy, Guy Elad, Kira Radinsky
The Web Conference ’19 – May 2019, San Francisco, California, USA
Query Driven Data Labeling with Experts: Why Pay Twice?
 
Eyal Dushkin, Shay Gershtein, Tova Milo, Slava Novgorodov
EDBT’19 – March 2019, Lisbon, 
Portugal
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