Vision AI Engineer

Job Description

You will work closely with engineers and project teams to ensure quality datasets and training outputs are delivered in a timely and traceable manner.

• Perform image and video annotation for computer vision use cases using external annotation platforms and software tools.
• Prepare, curate, label, and validate datasets for training, testing, and evaluation of computer vision models.
• Execute computer vision model training and retraining workflows using third-party AI software based on defined procedures and configurations.
• Support robotics, humanoid, and automation initiatives by facilitating software-based training workflows for manufacturing automation systems.
• Assist in collecting image, video, and related data samples from manufacturing or operational environments in accordance with defined guidelines.
• Conduct data quality checks to ensure annotated and collected datasets meet accuracy, consistency, and completeness requirements.
• Track dataset versions, annotation progress, and training outputs to ensure traceability and smooth handover to engineering teams.
• Collaborate with internal engineers, automation specialists, and project teams to understand data and training requirements.
• Document annotation guidelines, data preparation steps, and standard operating procedures.
• Support proof-of-concept and pilot activities by ensuring timely availability of required datasets and training outputs.
• Comply with internal data governance, security, and operational standards at all times.

• Bachelor’s degree, Diploma, or equivalent qualification in Engineering, Computer Science, or a related field. Fresh graduates are welcome to apply.
• Hands-on experience in image and video annotation for computer vision applications.
• Experience using annotation tools or third-party AI training software.
• Basic understanding of computer vision concepts such as object detection, image classification, segmentation, and video analytics.
• Ability to prepare, label, and validate datasets for training and testing purposes.
• Willingness to carry out hands-on data collection, including images, videos, and sample data, where required.
• Exposure to automation, robotics, humanoid systems, or manufacturing environments will be an advantage.
• Strong attention to detail and ability to follow defined processes and quality standards.
• Good communication and teamwork skills.