Senior Member of Technical Staff

eBay • San Jose, CA

3d • Onsite

About The Position

At eBay, 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. Senior Technical Staff Member, Applied Research (T27) San Jose, CA Position Overview eBay is looking for a Senior Member of Technical Staff, Applied Research to update the search stack and develop new conversational search and natural language query features. This role involves hands-on work as an individual contributor who can shift between applied research, quick prototyping, production deployment, and close collaboration with engineering and product teams. This position centers on improving how users convey shopping intent through natural language and how eBay interprets, retrieves, ranks, and responds to those signals in modern search experiences. The ideal candidate blends solid research instincts with practical production skills and is eager to transform new NLP and LLM capabilities into scalable systems that deliver clear customer and business results. Based in San Jose, the role partners with applied research, search engineering, product, and platform teams to improve discovery foundations and foster richer conversational experiences.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical area, or equivalent hands-on experience
• 8+ years of experience in applied research, machine learning, search, NLP, or related engineering roles
• Strong hands-on experience building and shipping production-quality ML, NLP, or search systems
• Deep expertise in one or more of the following areas: Dialogue-based search and information retrieval
• NLP, intent understanding, semantic parsing, or query reformulation
• Large language model applications for search, assistance, or question answering
• Ranking, retrieval, embeddings, or relevance optimization
• Strong coding and system development skills, with the ability to independently drive complex technical work from concept through production
• Demonstrated ability to evaluate technical tradeoffs across quality, latency, scalability, and maintainability

Nice To Haves

• Advanced degree such as an MS or PhD in Computer Science, Machine Learning, NLP, Information Retrieval, or a related field, or equivalent experience
• Experience modernizing search or discovery systems in ecommerce, consumer technology, or large-scale digital platforms
• Experience working on natural language query platforms, conversational interfaces, or LLM-powered product experiences
• Track record of translating research ideas into product impact through experimentation and iterative deployment
• Strong communication skills and the ability to guide technical direction across partner teams without formal authority

Responsibilities

• Build, prototype, and productionize solutions for conversational search and natural language query understanding
• Assist in updating the search stack across query understanding, retrieval, ranking, and response generation layers
• Develop methods for intent understanding, query rewriting, semantic retrieval, result grounding, and multi-turn refinement
• Partner with science and engineering teams to integrate data-informed approaches into production systems with strong latency, quality, and reliability characteristics
• Build and evaluate NLQ solutions that help buyers express complex shopping needs more naturally and get more relevant outcomes
• Build offline and online evaluation frameworks for conversational quality, retrieval efficiency, relevance, and customer impact
• Contribute technical depth on model selection, timely and system build, experimentation, and measurement
• Raise the technical bar through hands-on implementation, code reviews, build discussions, and cross-team collaboration

Benefits

• 401(k) eligibility
• various paid time off benefits, such as PTO and parental leave
• medical
• financial
• other benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior