Computer Vision Engineer: Mosquito Behavior Analytics

Monarch; Emeryville (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Monarch in Emeryville, CA, is hiring for a full-time in-office role focused on developing and validating methods to detect and track mosquitoes and other insects in top-mounted behavioral assays. You will derive behavioral metrics such as occupancy, trajectories, and dwell times, and build robust labeled datasets across labs and conditions.

You will work with entomologists and lab teams to optimize camera setup, assay geometry, and measurement labels while ensuring transparent, auditable

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.

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.

Skills

Object detection

Multi-object tracking

Segmentation

Pose/trajectory analysis

Python

PyTorch

OpenCV

Clear communication

Tools

PyTorch

OpenCV

Job description

Monarch in Emeryville, CA, is hiring for a full-time in-office role focused on developing and validating methods to detect and track mosquitoes and other insects in top-mounted behavioral assays. You will derive behavioral metrics such as occupancy, trajectories, and dwell times, and build robust labeled datasets across labs and conditions.

You will work with entomologists and lab teams to optimize camera setup, assay geometry, and measurement labels while ensuring transparent, auditable