採用
Required Skills
Machine Learning
Deep Learning
Natural Language Processing
Python
Scala
Java
SQL
Apache Spark
Big Data
At e Bay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
Our Recommendations team works on delivering item recommendations at scale and in near real time to our buyers on our website and native app platforms. Recommendations are a core part of how our buyers navigate e Bay’s vast and varied inventory. Our team develops state-of-the-art recommendations systems, including deep learning based retrieval systems for personalized recommendations, machine learned ranking models, as well as advanced MLOps in a high volume traffic industrial e-commerce setting.
We are exploring a new generation of recommender systems powered by Large Language Models and other emerging paradigms like GenAI. We are looking for an Applied Scientist and innovator who can drive state of the art ML modeling and get systems into production at e Bay scale as we expand our recommendations to live video auctions for e Bay Live.
What you will accomplish:
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Build data pipelines needed to support user input, recall and ranking, model training and inference, working with architects and other engineering peers.
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Track the fast paced world of AI and apply innovative techniques to unique and large data sets of unstructured multimodal data representing e Bay's vast and varied inventory, and millions of users.
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Develop and deploy innovative models in the context of recommender systems.
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Deploy big data technology and large scale data pipelines to create magical AI applications and user experiences.
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Have a real impact on how shoppers interact with one of the world's largest e-commerce marketplaces to find what they love every day.
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Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations.
What you will bring:
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MS in Computer Science or related area with 3 years of relevant work experience (or BS/BA with 5 years) in ML / AI / Data Engineering
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Experience in production engineering practices and software development in an OO language (Scala, Java, etc.)
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Experience in AI applied research, preferably in Natural Language Processing (NLP), deep learning, and industrial recommender systems
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Experience in big data processing and analysis, e.g. Hadoop, SQL, Spark, Pyspark is required
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Experience with using cloud services, big data pipelines and databases
Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talentebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.
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About eBay

eBay
PublicBuy, sell, and discover.
10,001+
Employees
San Jose
Headquarters
Reviews
3.8
5 reviews
Work Life Balance
4.2
Compensation
2.5
Culture
4.0
Career
2.8
Management
3.5
Pros
Good work-life balance
Great culture and environment
Nice colleagues and supportive people
Cons
Limited opportunities for growth
Old technology and systems
Call quotas and difficult customers
Salary Ranges
2,741 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Science Analyst 2
1 reports
$174,200
total / year
Base
$134,000
Stock
-
Bonus
-
$174,200
$174,200
Interview Experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 75%
Negative 25%
Interview Process
1
Application Review
2
Online Assessment (CodeSignal)
3
Technical Phone Screen
4
Technical Interview Rounds
5
Final Review
Common Questions
Coding/Algorithm
Technical Knowledge
Problem Solving
Data Structures
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