Senior Computer Vision Engineer

3 days ago

Greater Toronto Area, Canada Talent Seed Full time

*Riyadh Based* - This role requires relocation to Riyadh, KSA


Our client seeks a Senior Computer Vision Engineer. The role involves hands-on CV/ML software development and deployment, from understanding the product requirements and defining Computer Vision functional specs to designing, developing, and deploying CV/ML models in production at scale.


You will be responsible for

  • Solving object detection, positioning, instance segmentation, and tracking.
  • Development of algorithms and models to extract different features from videos captured by mobile mapping equipment and satellite data.
  • Deployment of computer vision algorithms and ML models.
  • Work closely with a cross-functional team of data scientists, software engineers, and product managers to define project requirements and deliver solutions.
  • Mentor junior engineers and provide technical leadership in computer vision and machine learning projects.
  • Conduct performance analysis and fine-tune models for optimal performance.
  • Stay up-to-date with the latest advancements in machine learning and computer vision technologies.


The ideal candidate has the following attributes:

  • MS in computer vision, machine learning, AI, applied mathematics, data science, or related technical fields or BS with 5+ years experience in Computer Vision/Machine Learning
  • Hands-on experience in developing new learning algorithms for one or more computer vision tasks such as object detection, object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation, adversarial and generative models, etc., and representational learning with a varied amount of data – from a few samples to a very large dataset.
  • Experience with deep learning, object detection, and image classification is essential.
  • Experience with YOLO is highly desirable.
  • Ability to train and debug deep learning systems – from defining datasets and evaluation metrics, model training, deployment, failure characterization, and iterative improvement
  • Strong programming skills and development experience with Python and ML/DL frameworks such as Tensorflow, Pytorch, etc.
  • Deep insights into data characteristics and the ability to map those to appropriate model architecture.

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