Integration Engineer

Exasoft; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Exasoft in Singapore is seeking an experienced ML Platform / Integration Engineer to design, build and support reliable AI/ML platforms and integrations for computer vision solutions. The role focuses on productionising AI/ML apps, deploying robust pipelines, and ensuring scalable, production-ready systems.

You will work with IT on infrastructure, packaging services, and implementing CI/CD, monitoring, and runbooks.

Qualifications

• 3–8 years of relevant experience in software engineering, platform engineering, or system integration.
• Diploma or Degree in Computer Science, Software Engineering, Information Technology, or a related field.
• Experience developing and integrating services and APIs.
• Experience with Linux, containers, version control, automated testing and CI/CD.
• Strong troubleshooting skills across application and infrastructure environments.
• Good technical documentation and communication skills.

Responsibilities

• Develop and maintain Computer Vision services, APIs, configurations and error-handling mechanisms.
• Package ML services and models for controlled deployment, versioning and rollback.
• Build and maintain automated testing, CI/CD pipelines and release processes.
• Implement health checks, structured logging, monitoring and operational diagnostics.
• Work closely with IT teams on infrastructure, connectivity, certificates, access and environment requirements.
• Support staging and production deployments, including troubleshooting and incident investigation.
• Troubleshoot issues across application, ML model and infrastructure layers.
• Prepare deployment guides, technical documentation, runbooks and operational handover materials.
• Ensure solutions follow relevant security, privacy, access-control and change-management requirements.

Skills

CI/CD

Troubleshooting

API development

Documentation

Education

Bachelor's/Diploma in CS/IT

Tools

Linux

Docker/Containers

Version control (Git)

CI/CD pipelines

Kubernetes

Azure cloud platforms

Job description

We are looking for an experienced ML Platform / Integration Engineer to design, build and support reliable platforms and integrations for AI and Computer Vision solutions.

The role will focus on productionising AI/ML applications, building robust deployment and integration processes, and ensuring solutions are scalable, supportable and ready for production environments.

Key Responsibilities

• Develop and maintain Computer Vision services, APIs, configurations and error-handling mechanisms.
• Package ML services and models for controlled deployment, versioning and rollback.
• Build and maintain automated testing, CI/CD pipelines and release processes.
• Implement health checks, structured logging, monitoring and operational diagnostics.
• Work closely with IT teams on infrastructure, connectivity, certificates, access and environment requirements.
• Support staging and production deployments, including troubleshooting and incident investigation.
• Troubleshoot issues across application, ML model and infrastructure layers.
• Prepare deployment guides, technical documentation, runbooks and operational handover materials.
• Ensure solutions follow relevant security, privacy, access-control and change-management requirements.

Requirements

• 3–8 years of relevant experience in software engineering, platform engineering, system integration or related areas.
• Diploma or Degree in Computer Science, Software Engineering, Information Technology, or a related field
• Practical experience developing and integrating services and APIs.
• Experience with Linux, containers, version control, automated testing and CI/CD.
• Good understanding of monitoring, logging, databases, networking and production support.
• Strong troubleshooting skills across application and infrastructure environments.
• Good technical documentation and communication skills.

Nice to Have

• Experience with Kubernetes and Microsoft Azure.
• Exposure to GPU workloads, video streaming or on-premises deployments.
• Experience with ML inference technologies such as ONNX, TensorRT or Triton.
• Previous experience supporting Computer Vision or production AI/ML workloads.