Computer Vision Engineer

Employment Type: Temporary

Duration: 6–12 Months

What You'll Gain

• Exposure to the complete computer vision pipeline, from raw data collection and annotation through model deployment.

• Mentorship from computer vision engineers building production-scale perception systems.

• Hands-on experience with YOLO, PyTorch, 3D reconstruction, and modern perception workflows.

• A portfolio of real-world work—including datasets, annotation tools, reconstruction pipelines, and model contributions—that directly supports future machine learning and computer vision careers.

What You'll Do

• Annotate and perform quality assurance on image and video datasets for object detection, segmentation, and classification, while building tooling to scale annotation workflows.

• Work on 3D reconstruction projects using photogrammetry and Gaussian Splatting, exploring applications in AR/VR and autonomous systems.

• Develop Python tools to:

  • Convert annotation formats

  • Validate label integrity

  • Generate dataset statistics

• Help define and refine labeling schemas and class taxonomies as new edge cases emerge.

• Run baseline YOLO training experiments to evaluate dataset quality and identify labeling deficiencies.

• Document annotation standards, workflows, and edge-case decisions.

Required Qualifications

• Recent graduate with a degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or a related field.

• Working knowledge of Python and common computer vision libraries such as NumPy and OpenCV.

• Strong attention to detail and the patience required for precision-oriented work.

Preferred Qualifications

• Hands-on experience with YOLO or PyTorch.

• Familiarity with one or more of the following:

  • 3D reconstruction

  • Segmentation masks

  • Model-assisted labeling workflows

• Interest in augmented reality (AR), virtual reality (VR), SLAM, or autonomous systems.