Posted 16 days ago
Applied Researcher 3 - Staff
@ eBay Canada Technology
Toronto, Ontario
Overview
eBay Canada Technology is hiring a Staff Applied Researcher on its Applied Science team in Toronto, a hybrid role requiring 3 office days per week. The role develops and deploys computer vision and multimodal AI models, adapting foundation models to domain-specific marketplace problems at scale. The posting describes a full-time position and leading ambiguous research from investigation to production.
Responsibilities:
- Develop and deploy visual and multimodal machine learning models at scale
- Design end-to-end training and inference pipelines for production AI systems
- Lead research on visual perception and multimodal AI
- Adapt foundation models to specialized domain problems
- Partner with product and engineering to build technical roadmaps
Requirements summary:
- PhD or M.S. in computer science, machine learning or a related field
- PhD plus 3 years or M.S. plus 4 years building vision or multimodal systems
- Hands-on experience fine-tuning and deploying vision-language models
- Strong Python and PyTorch or TensorFlow skills
- Experience with PySpark, SQL and Hadoop
- Excellent communication skills with senior stakeholders
Tools & skills
Source and dates
Employer career site / ATS feed · workday
- Employer posting date
- 2026-10-22
- First seen by our source
- 2026-10-22
- Source record updated
- 2026-11-03
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 3+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Doctorate (preferred), Master’s degree (required) |
| Fields of study | Computer Science, Electrical Engineering, Machine Learning, Applied Mathematics |
Summary and details written by AI from the posting; the employer’s posting is the authority.
eBay Canada Technology
| Field | Value |
|---|---|
| Open jobs on Jobsy | 21 |
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 days
About the role and the team
In the role of Applied Researcher 3 within the Global Focus Categories on the Applied Science team, you will develop new computer vision and multi-input 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, image and multimodal intelligence, and large-scale machine learning systems. You will work across a continually evolving portfolio of projects and areas of challenge 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 a Staff level Applied Researcher, 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 advanced image and multimodal core models. Develop specialized architectures, training approaches, data strategies, evaluation methods, and supporting systems to adapt them for challenging real-world applications.
As the Staff Applied Researcher on the team, your role includes helping develop the technical direction and identifying new opportunities for applied research. You will lead ambiguous problems from initial investigation through production impact, influence senior technical and product collaborators, 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
- PhD + 3 or more years of experience OR M.S. + 4 year of experience building computer vision and/or multimodal systems for large-scale applications
- 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
- Demonstrated expertise in scalable machine learning infrastructure, distributed training, model serving, and production monitoring, with extensive experience leveraging PySpark, SQL, and Hadoop for large-scale data processing
- 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 [email protected]. 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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