Machine Learning Engineer

eBay   •  

San Jose, CA

Industry: Technology


Not Specified years

Posted 98 days ago

This job is no longer available.

Looking for a company that inspires passion, courage and imagination, where you can be part of the team shaping the future of global commerce? Want to shape how millions of people buy, sell, connect, and share around the world? If you’re interested in joining a purpose driven community that is dedicated to creating an ambitious and inclusive workplace, join eBay – a company you can be proud to be a part of.

Work as a machine learning engineer in the Shopping Experience Applied Research organization at eBay. Work involves performing top down and bottom up applied research in the areas of information retrieval, natural language processing, data insights and analytics and graph processing. Work also involves building production facing user components which heavily rely on data mining and machine learning. The candidate is expected to be able to communicate with technical and non-technical audiences including leadership, quality engineering, software engineering and product as well as program management.

Shopping Experience Applied Research Team at eBay is looking for a strong applied researcher / machine learning engineer.  The team works on heterogeneous data sets (behavioral, transaction and crawled data) and focuses on solving applied problems using Natural Language Processing, Text Mining, Data Mining & Machine Learning.  The ideal candidate will have a nice blend of science and engineering skills, proven track record of solving critical business problems through data science and strong analytical/quantitative and engineering skills.  The candidate will be expected to be strong at communication and capable of cross group collaborations.  Experience in several of Spark/Hadoop, information extraction, text mining, information retrieval, machine learning, NLP is highly desirable.

  • eBay is one of the largest online marketplaces in the world servings 100's of millions of customers.  These customers engage with the platform and buy the most diverse merchandise from sellers all over the world.
  • The inventory ranges from a consumer selling her used t-shirt to some iconic merchandise sold by a few of the biggest brands on the planet.  Due to the diverse nature of our sellers and corresponding inventory, we have a treasure trove of unstructured offers.
  • The Shopping Experience Applied Research Team's charter is to conduct applied research in various domains of shopping experience.  The problems span recommendation systems (search/browse recommendations, top picks, evidence signals), graph mining, product reviews classification and ranking, large-scale duplicate detection as well as competitive analytics and data-driven tools.

What are we looking for?

The ideal candidate has a nice blend of engineering and science skills.

  • Previous experience with either IR, NLP, text mining, machine learning or big data mining is highly desirable.
  • Passion for leveraging technical solutions aligned with long term strategy with incremental deliverable outputs would be appreciated.
  • Strong interpersonal communication and collaboration skills
  • Ability to work on data mining , data science projects with application engineering, quality engineers and product management.
  • Ability to mentor other data scientists and engineers.
  • Passion to stay on the cutting edge of data science.