Urban Traffic Object Detection
Annotated street-level images by drawing bounding boxes around objects
Hire this AI Trainer
Sign in or create an account to invite AI Trainers to your job.
I have experience contributing to AI training data projects through platforms such as Appen, where I worked on tasks involving text classification, search relevance evaluation, and dataset validation for natural language processing models. My role involved reviewing and labeling data according to detailed annotation guidelines, ensuring high accuracy and consistency in the datasets used to train machine learning systems. I also performed quality checks and helped improve dataset reliability by identifying ambiguous or incorrect labels. In addition to annotation work, I have a strong background in AI and Machine Learning through academic and project experience. I have worked on projects involving anomaly detection, graph-based root cause analysis, and LLM-powered applications, where I handled tasks such as data preprocessing, labeling training datasets, and evaluating model outputs. My experience with Python, data analysis, and machine learning workflows allows me to understand how high-quality labeled data directly impacts model performance, enabling me to contribute effectively to AI training data projects.
Annotated street-level images by drawing bounding boxes around objects
Bachelor of Technology, Computer Science with Internet of Things
Machine Learning Engineer
Software Developer