Software Engineer, Internal Tools & Data Pipelines

CORTEX AI PTE LTD; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

CORTEX AI PTE LTD is seeking a software engineer to own applications and pipelines that move data from capture to review and delivery, and to build ML services that assist labeling and automated checks. You'll tackle full-stack apps, backend services, cloud infrastructure, and automation, working closely with operators, engineers, and researchers to ship first versions and improve them with feedback.

You will design APIs, data models, and monitoring to ensure reliable production systems across

Qualifications

• Shipped software in professional, internship, or open-source contexts.
• Experience building React/TypeScript frontends and Python services.
• Experience deploying to cloud (AWS, GCP, or Azure) and debugging.
• Ability to design APIs, schemas, and data models.
• Clear communication, initiative, and documentation.

Responsibilities

• Build internal tools and dashboards for data quality and task progress.
• Create data pipelines moving video and sensor data to storage and tooling.
• Ensure deployment reliability with monitoring and recovery paths.
• Deploy ML models behind APIs and integrate LLM APIs into tools.
• Collaborate with users to prioritize problems and ship iterations.

Skills

Full-stack development

Cloud infrastructure

Usability & maintainability

Communication & initiative

User collaboration

Tools

Docker

CI/CD

Infrastructure as Code

Production monitoring

FFmpeg

Linux

Job description

CORTEX AI PTE LTD is seeking a software engineer to own applications and pipelines that move data from capture to review and delivery, and to build ML services that assist labeling and automated checks. You'll tackle full-stack apps, backend services, cloud infrastructure, and automation, working closely with operators, engineers, and researchers to ship first versions and improve them with feedback.

You will design APIs, data models, and monitoring to ensure reliable production systems across