aimlroles

Applied Researcher 2 - Multimodal AI

TCGplayer (Apply) Open · verified Oct 22, 2026
Hybrid Toronto Full-time Mid-level AI Research

At a glance

Mid-level AI Research role at TCGplayer (Apply). Toronto · full-time · CA$142,400–CA$190,100 base.

SalaryStated by TCGplayer (Apply)
CA$142,400 – CA$190,100
Base salary for this role, in CAD per year, as published in the posting.
This role, from TCGplayer (Apply)Our estimate for the market: CA$116,188–CA$162,688Median CA$129,625
Above the market median of CA$129,625 for mid-level AI research roles in Toronto.
Worked out from 10 postings that stated pay, median CA$129,625. Last updated Oct 17, 2026.
RoleAI Research
SeniorityMid-level
LocationToronto
WorkplaceHybrid
EmploymentFull-time
Base payCA$142,400–CA$190,100
PostedSep 29, 2026 · 3w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and launch vision or multimodal models for search, recommendations, video and live-streaming applications
  • Carry research projects from defining the problem and preparing data through testing, implementation and production
  • Improve model training, inference and evaluation workflows, including systems that coordinate multiple models and services
  • Assess model changes with designed metrics, offline and online tests, error reviews and ablation studies
  • Develop pipelines using foundation models, retrieval, tools and business logic for buyer and seller experiences

What you bring

  • A master's or doctoral degree in a technical field focused on computer vision, multimodal learning or AI
  • At least three years building computer vision or multimodal systems for large-scale applications
  • Practical experience training, adapting, assessing and deploying visual-language or other foundation-model systems
  • Working knowledge of Python and modern ML frameworks such as PyTorch or TensorFlow

Who this fits

This hands-on role suits someone who can take applied research from early problem framing through production and work closely with product, engineering and research partners. The position is based in Toronto and listed as hybrid.

From the employer

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.

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 Details

The 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.

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 talent@ebay.com. 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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