Henrik Whitman

Results-driven AI Data Annotation and Computer Vision Specialist with professional experience supporting the development of artificial intelligence, computer vision, and machine learning systems through high-quality image and video annotation, data validation, and AI model evaluation. Experienced in working with globally recognized AI organizations including Welocalize, Invisible Technologies, and Remotasks, contributing to projects involving computer vision, human-in-the-loop AI training, and dataset quality improvement. Demonstrated expertise in annotating complex visual datasets using Labelbox and CVAT, applying bounding boxes, polygon annotations, semantic segmentation, object tracking, and frame-by-frame video labeling techniques to create accurate training data for machine learning models.

Adept at following complex annotation guidelines, maintaining high consistency across large datasets, and performing rigorous quality assurance to ensure datasets meet production standards. Possess a strong academic foundation in Computer Science complemented by specialized industry training in AI operations, automation, and large language model evaluation. Experienced in collaborating with globally distributed teams, documenting annotation processes, identifying edge cases, and continuously improving annotation workflows to support the development of reliable and scalable AI systems.

Recognized for exceptional attention to detail, analytical thinking, adaptability, and the ability to consistently deliver high-quality work in fast-paced remote environments.

AI Data Annotation & Computer Vision Specialist - Welocalize - Remote

(2024-01)

Support the development of advanced artificial intelligence and computer vision systems by creating accurate, high-quality annotated datasets used to train and evaluate machine learning models. Work within globally distributed teams to ensure annotation accuracy, consistency, and compliance with project-specific quality standards while contributing to AI solutions deployed across multiple industries.

• Annotate complex image and video datasets for computer vision and machine learning applications using industry-standard annotation methodologies.
• Perform detailed frame-by-frame video annotation involving multiple moving objects while maintaining temporal consistency throughout video sequences.
• Create accurate bounding boxes, polygon annotations, semantic segmentation masks, and attribute labels to support object detection and scene understanding models.
• Identify, classify, and annotate objects, actions, environmental conditions, and object relationships according to detailed project specifications.
• Validate completed datasets through comprehensive quality assurance processes to ensure annotation accuracy and consistency.
• Detect annotation inconsistencies, classification errors, missing labels, and ambiguous cases before dataset delivery.
• Collaborate closely with AI engineers, project managers, and quality assurance teams to refine annotation guidelines and improve dataset quality.
• Document annotation challenges, complex edge cases, and workflow improvements to support continuous enhancement of annotation standards.
• Maintain confidentiality while handling proprietary datasets and sensitive AI training materials.
• Consistently meet project deadlines while maintaining high productivity and exceptional annotation quality.

AI Training & Automation Specialist - Invisible Technologies - Remote

(2024-01)

Contribute to enterprise AI development by evaluating AI-generated outputs, supporting large language model training, validating datasets, and improving automation workflows. Perform human-in-the-loop quality assurance activities designed to enhance AI reasoning, response quality, and operational efficiency.

• Evaluate AI-generated responses for factual accuracy, logical consistency, completeness, and policy compliance.
• Analyze complex prompts and provide structured feedback that supports continuous improvement of large language models.
• Perform annotation, validation, and quality assurance tasks across structured and unstructured datasets.
• Review AI outputs to identify inconsistencies, hallucinations, reasoning errors, and formatting issues requiring correction.
• Support workflow automation initiatives by applying standardized quality control procedures and documentation practices.
• Interpret detailed project guidelines while adapting quickly to evolving annotation requirements.
• Collaborate with multidisciplinary teams to ensure consistent delivery of high-quality AI training data.
• Maintain productivity and quality metrics while working independently in a fully remote environment.

AI Data Annotation Specialist - Remotasks - Remote

(2022-01 - 2023-12)

Worked on large-scale artificial intelligence and computer vision projects involving image annotation, video annotation, object detection, segmentation, and dataset preparation for machine learning models. Produced accurate, guideline-compliant annotations supporting AI systems across multiple domains.

• Annotated thousands of images and video frames using bounding boxes, polygon annotations, and semantic segmentation techniques.
• Performed object detection and classification across diverse datasets involving vehicles, pedestrians, infrastructure, consumer products, and environmental objects.
• Applied frame-by-frame annotation techniques to ensure consistent object tracking throughout video sequences.
• Conducted quality assurance reviews to verify annotation accuracy, completeness, and compliance with project guidelines.
• Corrected annotation inconsistencies and contributed to improving overall dataset quality.
• Adapted efficiently to multiple project types, annotation standards, and changing client requirements.
• Maintained excellent productivity while consistently meeting quality benchmarks and project deadlines.
• Collaborated effectively within remote teams to support successful project delivery.

Bachelor of Science - Computer Science - University of Nairobi