IRnow Sdn. Bhd. Hiring! Full Time Assistant Machine Vision Labeler in Selangor - Ricebowl

About the job

Why should you choose to work with IRnow solving manufacturer's problems?

IRnow provides you with conducive working environment focusing on getting things done. We go weekly for lunch and have up to two (2) days working from home. We are one team focused on bringing maximum value to the manufacturers. You will be trained and guided by our existing machine learning engineers. Newly received diploma holders are very welcome to embark on the IRnow (Industrial Revolution now) journey.

Company Description IRnow Sdn. Bhd. helps manufacturers address rising labor and energy costs and declining product prices through advanced automation and data-driven solutions. The company implements automatic visual inspection (AVI) systems capable of inspecting up to 300,000 parts per day without human intervention, and provides real-time monitoring and data analytics systems for machine, process, and maintenance parameters. IRnow also focuses on cutting energy consumption by monitoring power usage at multiple levels, sending alerts for abnormal spikes, and generating reports and recommendations for optimization. Your work place will be in Seri Kembangan.

Role Description The Assistant Machine Vision Labeler is a full-time, on-site role based in Selangor, Malaysia. The role focuses on preparing and labeling image datasets used to train and validate machine vision and automatic visual inspection systems. Day-to-day tasks include reviewing images captured from production environments, accurately annotating defects and object features, and maintaining consistent labeling standards according to project guidelines. The Assistant Machine Vision Labeler will collaborate with engineers and data specialists to refine labeling rules, perform basic quality checks on labeled data, and help organize datasets for model training and testing. The role may also involve documenting labeling procedures, supporting continuous improvement of labeling workflows, and assisting with simple data entry or report updates related to inspection performance.

Qualifications

• Ability to perform detailed visual inspection of images, with strong attention to accuracy and consistency in labeling tasks.
• Basic understanding of data labeling or annotation tools (e.g., bounding boxes, segmentation, classification tags) and willingness to learn new software.
• Comfort with computers and digital workflows, including organizing files, following naming conventions, and working with spreadsheets or simple databases.
• Good communication skills to work with engineers and project teams, and openness to feedback for improving labeling quality.
• Ability to focus on repetitive tasks for extended periods while maintaining high-quality standards and meeting deadlines.
• Interest in automation, machine vision, or Industry 4.0 technologies; prior exposure to manufacturing environments is an advantage.
• Secondary school, diploma, or equivalent qualification; technical or IT-related education is beneficial but not mandatory.
• Willingness to work on-site in Selangor, Malaysia, and to comply with all workplace safety and confidentiality requirements.

Thank you so much for your interest.

Kind regards,

Simon