Computer Vision Engineer

Responsibilities

• Develop and validate methods for detecting and tracking multiple mosquitoes in top-mounted behavioral-assay video
• Derive cumulative landing-zone occupancy, trajectories, spatial distribution, entry and exit rates, dwell time, and other interpretable behavioral features
• Build representative labeled datasets and error analyses across labs, cameras, lighting conditions, arenas, mosquito densities, and occlusion patterns
• Quantify confidence and route uncertain or anomalous results to efficient human review rather than silently producing a score
• Design visual overlays and quality-control tools that let scientists inspect how each measurement was produced
• Work with entomologists and lab teams to improve camera placement, assay geometry, capture standards, and the behavior labels that matter scientifically
• Develop and validate methods for detecting and tracking multiple insects in top-mounted behavioral-assay video
• Derive cumulative landing-zone occupancy, trajectories, spatial distribution, entry and exit rates, dwell time, and other interpretable behavioral features
• Build representative labeled datasets and error analyses across labs, cameras, lighting conditions, crop surfaces, insect densities, and occlusion patterns
• Quantify confidence and route uncertain or anomalous results to efficient human review rather than silently producing a score
• Design visual overlays and quality-control tools that let scientists inspect how each measurement was produced
• Work with entomologists and lab teams to improve camera placement, assay geometry, capture standards, and the behavior labels that matter scientifically

Qualifications

• Strong experience with object detection, multi-object tracking, segmentation, pose or trajectory analysis, or related computer-vision methods
• Strong Python skills and experience with PyTorch, OpenCV, or equivalent tools
• Experience building evaluation sets and choosing metrics that reflect the downstream use of a vision system
• Ability to build efficient video-processing pipelines and debug failures at the frame and sequence level
• Clear communication with domain scientists and software engineers

Desired Attributes

• Experience with small-object tracking, animal behavior, microscopy, or other visually difficult scientific video
• Experience with domain adaptation, weak supervision, active learning, or human-in-the-loop annotation
• Familiarity with camera calibration, experimental instrumentation, or cross-site capture standardization
• Interest in making scientific measurements interpretable and auditable

Our crop-protection work

Turn raw assay video into precise, reviewable measurements of what insects do over time. The work begins with detection and tracking, but the scientific outcome is a trustworthy behavioral record that can train and evaluate models.

Qualifications

• Strong experience with object detection, multi-object tracking, segmentation, pose or trajectory analysis, or related computer-vision methods
• Strong Python skills and experience with PyTorch, OpenCV, or equivalent tools
• Experience building evaluation sets and choosing metrics that reflect the downstream use of a vision system
• Ability to build efficient video-processing pipelines and debug failures at the frame and sequence level
• Clear communication with domain scientists and software engineers

Desired Attributes

• Experience with small-object tracking, animal behavior, microscopy, or other visually difficult scientific video
• Experience with domain adaptation, weak supervision, active learning, or human-in-the-loop annotation
• Familiarity with camera calibration, experimental instrumentation, or cross-site capture standardization
• Interest in making scientific measurements interpretable and auditable
• To learn more, visit monarchlabs.org