ML Engineering Tl/architect T27

Machine Learning Engineer (T27), Product Knowledge Science

Do you love data? Graphs? Machine Learning? Knowledgeable, collaborative co-workers? Come work at eBay and help us redefine global, online commerce!

Who Are We?

The Product Knowledge team is at the epicenter of eBay's Tech-driven, Customer-centric overhaul. Our team is entrusted with creating and using eBay's Product Knowledge - a vast Big Data system which is built up of listings, transactions, products, knowledge graphs, and more. Our team has a mix of highly proficient people from multiple fields such as Machine Learning, Data Science, Software Engineering, Operations, and Big Data Analytics. We have a strong culture of collaboration, and plenty of opportunity to learn, make an impact, and grow!

What Will You Do?

We are looking for exceptional Machine Learning Engineers to join us and help lead improvements, automation, and scaling of our data-heavy processes. Our Senior Researchers tackle such diverse and challenging projects on Image Quality scoring; Automatic Taxonomy Improvement; Entity Resolution of rich, hierarchical Entities; and Conflict Resolution between different representations of the same Entity. Further, they help us design these separate projects and envision how they come together to create and power new experiences that surprise and delight our Customers. If you love a good challenge, and are good at handling complexity - we'd love to hear from you!

eBay is an amazing company to work for. Being on the team, you can expect to benefit from:

• A competitive salary - including stock grants and a yearly bonus
• A healthy work culture that promotes business impact and at the same time highly values your personal well-being
• Being part of a force for good in this world - eBay truly cares about its employees, its customers, and the world's population, and takes every opportunity to make this clearly apparent

Job Responsibilities

• Collaborate with Management and Product Management on shaping the department's vision and roadmap
• Design, deliver, and maintain significant features in data pipelines, ML processing, and / or service infrastructure
• Seek scientifically valid solutions that deliver real value to eBay customers
• Carefully measure your output and impact in order to learn and improve over time
• Collaborate with Operations team to ensure the quality of any human-labeled data required
• Build Machine Learning models and data pipelines to deliver insightful yet practical solutions
• Mentor more junior peers, as well as review their work and provide frequent feedback and advice
• Promote Scientific rigor and standards, as well as code quality and craftsmanship within the team - especially among your less experienced peers
• Present key technical and novel research work in public forums and conferences
• Help interview and hire additional, exceptional teammates!

Minimum Qualifications

• BE/B.Tech with 10+ years of relevant Industry experience
• M.Sc. or Ph.D. in Computer Science, Statistics, Mathematics, or equivalent field with 7+ years of industrial experience in Applied Machine Learning
• Industrial experience with multiple of the following: classification, regression, NLP, clustering, Deep Learning / Neural Networks, Reinforcement Learning, or related
• Significant Experience in Production-grade coding in a high-level language such as Python or Java
• Experience in Big Data processing frameworks, e.g. Hadoop, SQL, Spark
• Excellent verbal and written communication and collaboration skills
• Thought leadership and mentoring skills

Additional Qualifications

• 5 or more related publications/patents in quality conferences or journals
• Open source tool building/commits to popular threads.
• Experience on Language models and KG building

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.