Summary
Arkar Aung is a Senior Machine Learning Engineer with 11 years of experience building production-grade ML systems, now focused on agentic LLM frameworks and evaluations. He has delivered end-to-end solutions across autonomous driving, utility digital twins, solar-cell defect detection, and large-scale ML platforms, combining deep learning research with cloud-native engineering. At Grab he improved ML deployment and discoverability while researching budget-conscious LLM fine-tuning; at FireVisor he cut training costs and annotation time substantially through pipeline automation. Comfortable across Kubernetes, AWS SageMaker, point-cloud and computer vision models, he blends hands-on model development with systems design to drive measurable cost and performance gains. Based in Australia and self-described as a curious practitioner, he brings a track record of turning research prototypes into robust, scalable products.
11 years of coding experience