Data Annotator at Focal Systems (2022-01 – Present)
Data annotation for AI models in autonomous retail checkout systems
- Annotates large datasets involving image and text data to train AI models used for autonomous retail checkout systems
- Collaborates closely with AI researchers to understand requirements to provide annotated data suitable for model training, accuracy, and improvement
- Reviewed and refined annotations to ensure high levels of consistency, quality, and precision across datasets
- Generates comprehensive multiple choice questions used to train AI models for various customers and retail applications
- Assisted in performing quality control checks on datasets to ensure compliance with project specifications and guidelines
Content Annotator & Researcher at Tagtog (2021-06 – 2021-12)
Data annotation and analysis for healthcare and financial AI models
- Worked on various data analysis projects for healthcare and financial related AI models
- Assisted in user annotation projects, focusing on labeling medical research and financial documents to aid in AI processing and interpretation
- Provided feedback on the performance of AI models based on annotated datasets, helping improve accuracy and knowledge extraction capabilities
AI Data Specialist at CloudFactory (2020-03 – 2021-05)
Data annotation project leadership for autonomous driving and healthcare AI models
- Led data annotation projects for machine learning models in autonomous driving and healthcare sectors
- Analyzed and managed various datasets associated with training computer vision models for autonomous driving
- Conducted quality checks on natural data ensuring compliance with the specifications provided by AI researchers
- Developed data generative strategies to optimize the performance of computer vision and natural language processing models
Data Annotator & Reviewer at Snorkel AI (2019-04 – 2020-02)
Multi-modal dataset development and quality control for AI training
- Contributed to the development of multi-modal datasets for AI training by annotating text and images
- Collaborated with leading AI research teams to ensure the datasets were accurately labeled, enhancing AI model performance
- Generated and document question-specific consensus rules for AI models general knowledge annotated data
- Conducted final reviews and quality control measures on large datasets to ensure data accuracy and readiness for AI model training
Data Labeling Specialist at Humainly (2018-08 – 2019-03)
Multilingual data annotation and quality assurance for AI models
- Annotates datasets in various languages, including French and English, to help train multilingual AI models
- Managed quality assurance processes for annotated text data, ensuring consistency and correctness
- Assisted in the development of sentiment datasets, creating questions and consensus rules for training AI models
- Provided feedback on the performance of AI models annotations and labeled data, contributing to model adjustments and fine-tuning
AI Data Trainer at Enlabeler (2017-09 – 2018-07)
Data annotation services for sentiment analysis and text classification projects
- Provided extensive data annotation services for annotated text data, ensuring consistency, quality, and correctness
- Conducted extensive data annotation and quality reviews for AI projects involving sentiment analysis and text classification
- Worked and helped review large text datasets to enhance AI natural language processing models
- Developed training datasets by evaluating and annotating text from diverse sources, ensuring the models ability to recognize different patterns and behaviors
- Provided in-depth reviews and recommendations on annotation guidelines, improving internal processes for subsequent projects
