Edge & Cloud Vision ML Engineer

Confidential Jobs; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Confidential Jobs is seeking a Machine Learning Engineer to own the productionisation of computer vision models, bridging model science and software engineering. You will deploy and optimize CV models across cloud and edge environments, while ensuring reliability and scalable serving architectures.

The role requires hands-on experience with ML systems, model versioning, and collaboration with cross-functional teams to deliver production-grade solutions.

Qualifications

• Bachelor’s or Master’s in Computer Science, Electrical Engineering, Machine Learning, or related field.
• 4+ years of experience in machine learning engineering, with production deployments to your name.

Responsibilities

• Deploy and maintain model serving infrastructure across cloud and edge environments.
• Optimise models for deployment: TensorRT, INT8/FP16, and edge ensemble fusion.
• Validate latency/throughput trade-offs and production rollout criteria.
• Manage model versioning and coordinated rollout across cloud and edge devices.
• Build end-to-end inference pipelines from input to structured output.
• Ensure inference reliability and graceful degradation in field conditions.
• Define integration contracts for downstream software systems.
• Design and maintain evaluation frameworks and active learning pipelines.
• Collaborate with CV Scientists on handoff requirements and with Software Engineers on API integration.
• Communicate performance and limitations of inference systems to stakeholders.

Skills

Python

Deep learning

Computer vision

Model deployment

Communication

System thinking

Education

Bachelor's or Master's in CS/EE/ML

Tools

AWS

Docker

Git

SageMaker

MLflow

Jetson

Job description

Confidential Jobs is seeking a Machine Learning Engineer to own the productionisation of computer vision models, bridging model science and software engineering. You will deploy and optimize CV models across cloud and edge environments, while ensuring reliability and scalable serving architectures.

The role requires hands-on experience with ML systems, model versioning, and collaboration with cross-functional teams to deliver production-grade solutions.