Internal Tools & Infra Engineer: Data Pipelines & ML

CORTEX AI PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

Cortex AI PTE. LTD. is seeking a software engineer to own end-to-end data pipelines, applications, and ML services from design to deployment.

You will work on internal tools, analytics dashboards, and automation to move video, sensor data, and metadata through capture to delivery, with a focus on reliability and scalability. You will collaborate with operators, engineers, and researchers to prioritize problems, ship first versions, and improve them continuously.

Qualifications

• Shipped working software through professional work, internships, open-source, or projects.
• Able to design APIs, database schemas, and data models connecting front-end and back-end services.
• Experience deploying and debugging applications on cloud platforms (AWS, GCP, or Azure).
• Familiarity with building reliable, maintainable software with good tests and documentation.

Responsibilities

• Build internal tools and dashboards to monitor task progress and data quality.
• Create APIs and pipelines moving video, sensor data, and metadata into storage and tools.
• Ensure releases are repeatable with monitoring and recovery paths for failed jobs.
• Deploy ML models behind APIs and integrate LLM APIs into internal tools.
• Collaborate with operators, engineers, and researchers to prioritize problems and iterate.

Skills

Full-stack development

React

Python services

Cloud infrastructure

APIs design

Data pipelines

Usability

Communication

Tools

Docker

CI/CD

Infrastructure as code

Monitoring

Job description

Cortex AI PTE. LTD. is seeking a software engineer to own end-to-end data pipelines, applications, and ML services from design to deployment.

You will work on internal tools, analytics dashboards, and automation to move video, sensor data, and metadata through capture to delivery, with a focus on reliability and scalability. You will collaborate with operators, engineers, and researchers to prioritize problems, ship first versions, and improve them continuously.