Senior Software Engineer, Machine Learning, Debug

• Design, train, and deploy deep learning models to visually analyze mosquitoes in our production process.
• Build high-accuracy object detection and image segmentation pipelines to count mosquito pupae from complex, real-world image data.
• Leverage environmental data and biological parameters to model mosquito population dynamics, ultimately optimizing our mosquito release strategies and schedules.
• Take ownership of the full machine learning lifecycle and transition models from local research prototypes into scalable, highly available production environments.
• Work closely with entomologists, data scientists, and hardware engineers to leverage machine learning techniques to most effectively solve problems for the team.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with full-stack development, including back-end, such as Java, Python, GO, or C++ codebases, and front-end, such as JavaScript, TypeScript, HTML, or CSS.
• Experience developing computer vision or machine learning products.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• Experience with hacking hardware (e.g., Arduino, Raspberry Pi, etc.), and with other technologies (e.g., AS3, OpenCV, Android, Obj-C, etc).
• Experience deploying machine learning models on edge devices or in resource-constrained environments.
  
• Experience working in agricultural tech, bio-tech, or environmental science.
  
• Familiarity with spatial statistics or epidemiological modeling.
  

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with full-stack development, including back-end, such as Java, Python, GO, or C++ codebases, and front-end, such as JavaScript, TypeScript, HTML, or CSS.
• Experience developing computer vision or machine learning products.