Director, Buyer Experience AI R&D

eBay

15 - 20 years

25 - 30 Lacs

bengaluru

Posted:19 hours ago| Platform:

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Skills Required

computer science production engineering machine learning scala agile natural language processing research open source object oriented programming analytics

Work Mode

Work from Office

Job Type

Full Time

Job Description

This is an opportunity to:

Lead and manage a large team of applied researchers and engineers with deep expertise in natural language processing, large language models / Generative AI, recommender systems, and ML production engineering
Drive applied research strategy for the eBay buyer experience, and influence how people will interact with eCommerce in the future
Work with unique and large data sets of unstructured multimodal data representing eBays vast and varied inventory, and millions of users
Develop and deploy state of the art AI models
Deploy big data technology and large scale data pipelines
Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations
Create a culture of applied research, innovation, experimentation and engineering excellence

Qualifications

Advanced degree (MS or PhD) in Computer Science or a related field, with 15 years of experience in Machine Learning, AI, or large-scale engineering environments.
Proven track record of building and leading high-impact engineering and research teams, ideally within ML/AI-focused organizations.
Experience with a variety of data science and ML techniques, exposure to Natural Language Processing (NLP) and industrial-grade recommender systems, with a passion for solving real-world problems at scale.
Solid background in production-level engineering practices, including Agile methodologies and object-oriented programming (e.g., Scala, Java), in high-throughput environments.
Proven track record of having business impact with production grade cloud-native solutions, scalable data pipelines, and large-scale distributed databases.
A history of technical thought leadership through academic publications, patents, or contributions to open-source projects or technical blogs is highly desirable.

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