Applied Vision Researcher, Multimodal ML in Production

eBay; Toronto; On-site; CAD 118,000 - 158,000; Full time

Benefits offered by this job

RRSP eligibility

Medical benefits

Paid time off

Parental leave

Job summary

eBay is seeking an Applied Researcher 1 to advance our computer vision and multimodal capabilities. You will train, fine-tune, evaluate, and deploy models across search, recommendations, content generation, and video understanding.

You will collaborate with product, engineering, and research teams to translate business opportunities into scalable ML solutions, using Python, PyTorch, and TensorFlow, with a strong emphasis on rigorous experimentation and production readiness.

Qualifications

• PhD or MSc in CS/EE/ML with focus on computer vision or multimodal learning.
• 1+ years building CV or multimodal systems for large-scale apps, e.g., search, recommendations, video.
• Strong understanding of CV and multimodal techniques like detection, segmentation, classification.
• Hands-on experience training and deploying vision-language models and foundation-model systems.

Responsibilities

• Develop and deploy CV or multimodal ML models for production across search, recommendations, and video.
• Lead through problem framing, data prep, experimentation, evaluation, and productionization.
• Build training, inference, and evaluation pipelines for modern AI systems.
• Apply rigorous experimentation and ablation studies to improve models.
• Collaborate with product, engineering, and research teams to translate opportunities into solutions.
• Communicate progress and trade-offs to stakeholders.

Skills

Python

Research methods

Communication

Multimodal learning

Education

PhD or MSc in CS/EE/ML

Tools

PyTorch

TensorFlow

Job description

eBay is seeking an Applied Researcher 1 to advance our computer vision and multimodal capabilities. You will train, fine-tune, evaluate, and deploy models across search, recommendations, content generation, and video understanding.

You will collaborate with product, engineering, and research teams to translate business opportunities into scalable ML solutions, using Python, PyTorch, and TensorFlow, with a strong emphasis on rigorous experimentation and production readiness.