Computer Vision Engineer
observable-space
Computer Vision Engineer
monarchcrops· R&D
About this role
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.
Key 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
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.
Key Responsibilities
• 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
To learn more, visit monarchlabs.org
Frequently Asked Questions
Is the salary disclosed for the Computer Vision Engineer position at monarchcrops?
The salary for this Computer Vision Engineer role at monarchcrops is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Computer Vision Engineer position at monarchcrops located?
This Computer Vision Engineer role at monarchcrops is based in Emeryville, California. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Computer Vision Engineer role at monarchcrops full-time or part-time?
This is listed as a FullTime position. It is posted as a Computer Vision Engineer role in the R&D department at monarchcrops.
Which team or department does the Computer Vision Engineer at monarchcrops belong to?
This Computer Vision Engineer position is part of the R&D department at monarchcrops. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Computer Vision Engineer position at monarchcrops?
Click the "Apply Now" button on this page. You will be redirected to monarchcrops's official application portal hosted on ashby where you can submit your application directly.
When was the Computer Vision Engineer job at monarchcrops posted?
This Computer Vision Engineer position at monarchcrops was posted on Sep 5, 2026. Apply as soon as possible — early applications are often reviewed first.
Computer Vision Engineer
monarchcrops
You'll be redirected to monarchcrops's official application page on Ashby ATS.