Applied Researcher 3

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.
Hybrid role, requires you to be in our Toronto office 3 daysAbout the role and the team
In the role of Applied Researcher 3 within the Global Focus Categories Applied Science team, you will develop new computer vision and multimodal AI solutions. These solutions will address complex problems across eBay’s global marketplace.
Our team focuses on challenges where current models and off-the-shelf methods fall short. We adapt and extend groundbreaking foundation models to solve specialized, domain-specific problems at scale.
The team works at the intersection of applied research, visual and multimodal intelligence, and large-scale machine learning systems. You will work across a continually evolving portfolio of projects and problem domains rather than specializing in a single application area.
Work has spanned personalized experiences and recommendations, content intelligence and attribute extraction, fine-grained visual recognition, anomaly detection, and multimodal understanding of marketplace inventory. Each problem brings different data, modeling, and system challenges, creating opportunities to explore new approaches and develop capabilities where established solutions fall short.
As an Applied Researcher 3, you will take problems from early investigation to production. You will research, build, train, fine-tune, evaluate, and deploy models and AI systems at scale. Collaborate with modern vision and multimodal foundation models. Develop specialized architectures, training approaches, data strategies, evaluation methods, and supporting systems to adapt them for challenging real-world applications.
As a Senior Researcher on the team, you will help shape technical direction and identify new opportunities for applied research, lead ambiguous problems from initial investigation through production impact, influence senior technical and product stakeholders, and mentor researchers across the team.
What you will accomplish
Develop and deploy visual and multimodal machine learning models for large-scale applications involving fine-grained recognition, visual understanding, content intelligence, retrieval, and decisioning
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 modelin
Lead research initiatives focused on visual perception technologies and multimodal artificial intelligence. Identify gaps in which existing models are insufficient
Develop innovative strategies and adapt foundation models for specific domain problems
Lead research and development in VLM training and fine-tuning, model distillation, 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.
3 or more years of experience building computer vision and/or multimodal systems for large-scale applications.
Demonstrated experience taking machine learning solutions from research and experimentation through production, including building training, evaluation, and inference pipelines and integrating models into both offline and online workflows.
Hands-on experience training, fine-tuning, evaluating, and deploying visual-language models or other modern foundation-model-based systems, including adapting these models to specialized applications and problem domains.
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, and production monitoring.
Strong proficiency in Python and modern machine learning frameworks such as PyTorch or TensorFlow, 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.
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, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at View email address on ca.hrm.tc. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay’s commitment to ensuring digital accessibility.
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