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Google

Senior Software Engineer, Machine Learning, Debug

Google

Published 16 May 2026
Singapore
Full Time
27500 - 275000 people

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Role Highlights

Languages used

Java
Python
GO
C++
JavaScript
TypeScript
HTML
CSS

Key skills

AI
Deep Learning
NLP
Information Retrieval
Machine Learning
Computer Vision
Image Segmentation
Computer Science
System Design
Full Stack
Backend
Frontend
PhD
Statistics
Modelling
Search
Data
Storage
Security
UI
Research

Tools, Libraries and Frameworks

OpenCV
Android

Description

The role involves designing, training, and deploying deep learning models to analyze mosquitoes within a production process. The engineer will build object detection and image segmentation pipelines to process complex image data. Responsibilities include leveraging environmental and biological data to model population dynamics and optimize release strategies. The position requires managing the full machine learning lifecycle from research prototypes to scalable production environments. Collaboration with entomologists, data scientists, and hardware engineers is essential to solve biological problems.

Required Qualifications and Skills

Candidates must possess a Bachelor's degree or equivalent practical experience. A minimum of 5 years of experience in full-stack development is required, covering both back-end and front-end technologies. Applicants must demonstrate experience in developing computer vision or machine learning products. Proficiency in English is required for this role.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

Google

Size

275773

Website

goo.gle

HQ

Mountain View, US

Public/Private

Public Company

Description

At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.

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