Geospatial AI Engineer for Satellite Insights

ST Engineering; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

ST Engineering Geo-Insights Pte Ltd is seeking a Geospatial Solutions Developer to design, implement, and train machine learning algorithms that turn raw satellite remote sensing data into actionable geospatial insights.

The role requires a strong background in Electrical Engineering or Computer Science, at least five years of relevant experience, and proficiency with Python, ML libraries (OpenCV, Scikit-learn, PyTorch, LangChain), and app frameworks like Flask or NodeJS, plus containerization.

Qualifications

• 5+ years of relevant experience.
• Proficient in machine learning and deep learning technologies.
• Proficient in python programming with libraries such as OpenCV, Scikit-learn, PyTorch, and LangChain.
• Familiar with Flask, NodeJS or other app frameworks, and containerization.
• Knowledge of Large Language Models and Retrieval Augmented Generation is a plus.

Responsibilities

• Design, develop and train Machine Learning algorithms for geospatial applications.
• Review relevant publications to understand and apply cutting edge concepts to integrate into business products.
• Work closely with product, business development and sales teams to understand business goals and determine AI requirements.
• Work with software team to integrate developed algorithms into geospatial system products.

Skills

Geospatial AI

Machine Learning

Python

OpenCV

Scikit-learn

PyTorch

LangChain

Flask

NodeJS

Containerization

Education

Electrical Engineering / Computer Science background

Tools

Docker

Kubernetes

Job description

ST Engineering Geo-Insights Pte Ltd is seeking a Geospatial Solutions Developer to design, implement, and train machine learning algorithms that turn raw satellite remote sensing data into actionable geospatial insights.

The role requires a strong background in Electrical Engineering or Computer Science, at least five years of relevant experience, and proficiency with Python, ML libraries (OpenCV, Scikit-learn, PyTorch, LangChain), and app frameworks like Flask or NodeJS, plus containerization.