Senior AI Engineer, Geospatial ML & MLOps

ST Engineering; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive remuneration

Comprehensive benefits

Job summary

ST Engineering Geo-Insights Pte Ltd is seeking a Senior AI Engineer to provide technical leadership in designing, developing, and deploying production-grade AI solutions for geospatial applications. You will architect scalable ML systems and work with software engineers to integrate AI components into end-to-end platforms.

You will own model performance and system reliability, driving MLOps practices, deployment, monitoring, and continuous improvement, while mentoring engineers and guiding

Qualifications

• 5+ years of production ML experience.
• Strong ML/DL foundation and model optimization.
• Proficient in Python and ML frameworks PyTorch / scikit-learn.
• Experience deploying ML services with API development and containers.
• Familiarity with geospatial data and MLOps is a plus.
• Mentor engineers and collaborate across teams.

Responsibilities

• Lead architecture, development, and deployment of production ML solutions for geospatial apps.
• Architect scalable ML systems and integrate AI components into end-to-end platforms.
• Own model performance and reliability through MLOps, deployment, and monitoring.
• Collaborate with product, business, and sales to translate objectives into technical requirements.
• Mentor engineers and provide technical support across pre- and post-sales activities.

Skills

Machine Learning

Deep Learning

Python

PyTorch

scikit-learn

OpenCV

API development

Docker

MLOps

Mentoring

Education

Bachelor's or higher in CS/EE

Tools

Flask

FastAPI

Node.JS

Job description

ST Engineering Geo-Insights Pte Ltd is seeking a Senior AI Engineer to provide technical leadership in designing, developing, and deploying production-grade AI solutions for geospatial applications. You will architect scalable ML systems and work with software engineers to integrate AI components into end-to-end platforms.

You will own model performance and system reliability, driving MLOps practices, deployment, monitoring, and continuous improvement, while mentoring engineers and guiding