Applied Researcher 3 Multimodal AI

At eBay were more than a global ecommerce leader were changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. Were 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. Were 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.

About the role and the team:

As an Applied Researcher in the Computer Vision group you will develop the multimodal intelligence that powers how buyers find inventory. You will build high-quality listings for sellers and improve eBays shopping experiences across search recommendations content generation live streaming and video.

This team works at the intersection of visual computing multimodal data integration and large-scale machine learning systems. We build and deploy production models and agentic pipelines that understand visual textual and other multimodalsignals improve retrieval and ranking generate and transform content and enable new product experiences at global scale. The work spans foundational model development orchestration of complex inference and training systems and close partnership with product and engineering leaders to translate research into measurable business impact.

In your role as an Applied Researcher 3 you will advance eBays multimodal and vision capabilities in order to support large-scale applications.
You will own the build training fine-tuning evaluation and deployment of brand-new models across a range of problem spaces including search recommendations content generation and video understanding.

As a Senior Researcher on the team you: help shape the technical direction vision and multimodal stack; influence senior stakeholders and mentor researchers.

What you will accomplish:

• Develop and deploy visual recognition and multimodal machine learning models for large-scale production applications across search recommendations video and live streaming.
• Design and optimize end-to-end training and inference pipelines for modern AI systems including orchestration of multiple models and services in production environments.
• Advance core capabilities in classical and modern vision and multimodal problem spaces such as detection segmentation classification metric and contrastive learning and visual-language modeling.
• Architect build and improve agentic VLM-powered solutions that combine models tools and business logic to deliver scalable user experiences.
• Lead research and development in VLM training and fine-tuning model distillations reinforcement learning and other components of the modern AI stack.
• Partner closely with product managers engineers designers and applied scientists to translate ambiguous business opportunities into robust technical roadmaps and delivered solutions.
• Communicate technical direction trade-offs and results clearly to cross-functional stakeholders including director-level leaders to drive alignment and informed decision-making.
• Mentor junior and senior team members raise the technical bar for experimentation and production excellence and contribute to a strong research and engineering culture.

Qualifications:

• Ph.D. or M.S. in Computer Science Electrical Engineering Machine Learning Applied Mathematics or a related technical field with a focus on computer vision multimodal AI or artificial intelligence.
• 5 or more years of experience building computer vision and/or multimodal systems for large-scale applications ideally in one or more of the following areas: search recommendations video and live streaming.
• Deep understanding of classical computer vision and multimodal learning techniques including detection segmentation classification representation learning and contrastive learning.
• Hands-on experience training fine-tuning evaluating and deploying visual-language models or other modern foundation-model-based systems and familiarity with the broader modern AI stack used to develop adapt and operationalize multimodal models.
• Practical experience with agentic AI workflows and VLM-powered pipelines in real-world production settings.
• Strong knowledge of scalable machine learning infrastructure and system design including distributed training model serving orchestration offline and online evaluation and production monitoring.
• Proficiency in Python and modern ML/data frameworks such as PyTorch TensorFlow and Spark with fluency in agentic coding and AI-assisted development workflows.
• Excellent verbal and written communication skills with a demonstrated ability to influence senior cross-functional stakeholders and collaborate effectively across research engineering and product organizations.
  
  

Additional Details

This job posting relates to an existing vacancy within eBay.

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