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 eBay's 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 multimodal signals, 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 the role of Applied Researcher 2 on the Computer Vision team, you will contribute to advancing eBay's vision and multimodal capabilities for large-scale applications.
You will work on the design, training, fine-tuning, evaluation, and deployment of models across problem spaces including search, recommendations, video and live stream understanding. This role is a hands-on role that takes end-to-end ownership of projects, apply rigorous methodology, and help bring high-quality ML solutions from idea to production.
What you will accomplish:- Develop and deploy computer vision or multimodal machine learning models for production applications across search, recommendations, video and live streaming.
- Take end-to-end ownership of research and applied ML projects, from problem framing and data preparation through experimentation, evaluation, implementation, and productionization.
- Design and improve training, inference, and evaluation pipelines for modern AI systems, including workflows that orchestrate multiple models and services.
- Apply strong experimental methodology and scientific rigor to model development, including metric design, offline and online evaluation, error analysis, and ablation studies.
- Contribute to core capabilities in classical and modern vision or multimodal problem spaces such as detection, segmentation, classification, contrastive learning, visual-language modeling, and multimodal retrieval.
- Build and improve agentic or VLM-powered pipelines that combine foundation models, retrieval, tools, and business logic to deliver scalable user and seller experiences.
- Partner with product managers, engineers, designers, and researchers to translate business opportunities into robust technical solutions.
- Communicate progress, technical trade-offs, and results clearly to cross-functional stakeholders.
Qualifications:- Ph.D. or M.S. in Computer Science, Electrical Engineering, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field with a focus on computer vision, multimodal learning, or artificial intelligence.
- 3 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 or live streaming.
- Strong understanding of classical computer vision and/or 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, including familiarity with the broader modern AI stack used to develop, adapt, optimize and operationalize multimodal models.
- Practical experience with agentic AI workflows and/or VLM-powered pipelines in applied or production settings.
- Experience with rigorous experimentation, evaluation methodology, and data-driven model iteration.
- Proficiency in Python and modern ML/data frameworks such as PyTorch and TensorFlow, with fluency in agentic coding and AI-assisted development workflows.
- Strong written and verbal communication skills, with the ability to collaborate effectively across research, engineering, and product organizations.
Additional DetailsThe base pay range for this position is expected in the range below:
C$142,400 - C$190,100
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including RRSP eligibility, various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
This job posting relates to an existing vacancy within eBay.
