Computer Vision Engineer

Monarch•Emeryville, CA

1d•Onsite

About The Position

We offer opportunities to do your life’s work while helping solve one of the most important technical and moral challenges of our time. Full-time, in-office in Emeryville, California. Our mosquito work Turn raw assay video into precise, reviewable measurements of what mosquitoes 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. 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.

Requirements

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
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

Nice To Haves

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
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

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