Senior Software Engineer, Machine Learning, Debug

Google; Singapore; On-site; SGD 150,000 - 180,000; Full time

Job summary

Google Singapore is seeking software engineers who can blend computer vision, machine learning, and full-stack development to tackle real-world public health challenges. The role spans design, training, and deployment of production ML models within large-scale systems, with collaboration across data scientists, hardware engineers, and domain experts.

You will work on projects at the intersection of vision, statistics, and software engineering, contributing to vector control and disease

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with full-stack development across back-end and front-end technologies.
• Experience developing computer vision or machine learning products.

Responsibilities

• 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.
• Model mosquito population dynamics using environmental data and biological parameters.
• Own the full ML lifecycle from research prototype to production.
• Collaborate with entomologists, data scientists, and hardware engineers to solve problems.

Skills

Full-stack development

Java

Python

Go

C++

JavaScript

TypeScript

HTML

CSS

Computer vision

Machine learning

Education

Bachelor's degree

Master's degree / PhD (preferred)

Tools

OpenCV

Arduino

Raspberry Pi

AS3

Android

Obj-C

Job description

Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.

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.

About The Job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will play a critical role in advancing our mosquito-born disease eradication program, directly contributing to vector control and public health initiatives. You will sit at the intersection of computer vision, statistical modeling, and software engineering. You will be solving complex biological problems and writing the production-ready code required to deploy those solutions into the real world.

Responsibilities

• 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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.