Computer Vision Annotation Associate — United States

About the Job

Our client is a venture-backed, high-growth artificial intelligence enterprise and machine learning solutions pioneer engineering next-generation autonomous systems, intelligent robotics, and predictive visual analytics. We are seeking an analytical, detail-oriented Computer Vision Annotation Associate to join our fully distributed Data Operations division. In this vital technical role, you will be responsible for creating the ultra-precise, high-quality ground truth datasets that train our advanced neural networks and deep learning models—interpreting, structuring, and labeling vast arrays of spatial and visual imagery.

Why Join Us

• Total Remote Work Autonomy: Work from wherever you are most productive, utilizing a cloud-based AI annotation tech stack, digital collaboration tools, and asynchronous engineering pipelines.

• Direct Artificial Intelligence Footprint: Bypass purely theoretical landscapes. Your daily data configurations, semantic segmentations, and bounding-box architectures will directly fuel machine learning models destined for live production environments.

Responsibilities

• High-Precision Data Annotation: Label and annotate expansive visual datasets (including high-resolution images, video feeds, and spatial sensor telemetry) using 2D/3D bounding boxes, polygons, polylines, keypoint tracking, and semantic segmentation masks.

• Data Quality Auditing & QA: Conduct rigorous quality assurance checks on pre-labeled data arrays, identifying and correcting tracking anomalies, misclassifications, or edge-case labeling variances to maintain a target 99%+ accuracy metric.

• Edge-Case Taxonomy Feedback: Collaborate directly with machine learning engineers and data scientists to refine internal labeling taxonomies, reporting edge cases or visual ambiguities to optimize model training rules.

• Annotation Software Optimization: Utilize and stress-test custom, cloud-based data annotation software interfaces, providing actionable UX feedback to internal tool-development teams to accelerate daily processing speeds.

• Pipeline Metrics Logging: Document and track shift processing metrics, managing project task backlogs within engineering tracking frameworks (such as Jira or spreadsheet pipelines).

Requirements

Required

• Education: Bachelor’s degree in Computer Science, Data Science, Information Technology, Mathematics, Cognitive Science, or an equivalent technical or business-quantitative discipline.

• Experience Level: 0 to 2 years of professional experience. This is an entry-level technical operational track; robust data internships, university machine learning lab projects, or an analytical background involving rigorous pattern recognition are highly valued.

• Visual & Spatial Acuity: Exceptional visual pattern recognition, a high degree of spatial intelligence, and an obsessive eye for detail required to maintain high analytical consistency over repetitive data structures.

• Proactive Remote Independence: A self-starting operator who thrives in a distributed team environment, manages daily processing schedules independently, and maintains highly transparent communication protocols.

Preferred

• Bilingual Language Fluency: Professional verbal and written proficiency in Korean is highly preferred to facilitate cross-border data alignment and coordinate seamlessly with international machine learning engineering hubs.

• Basic foundational familiarity with standard computer vision concepts, machine learning training cycles, or data labeling tools (such as CVAT, LabelImg, Labelbox, or Roboflow).

• Minimal, entry-level familiarity with command-line operating systems or basic Python script execution for dataset handling is a significant advantage but not mandatory.

Job Location & Details

• Visa Support: OPT / STEM OPT Validation & H1-B Sponsorship Provided

• Salary Range: $52,000 – $68,000 USD base structure + Model Deployment Performance Bonuses, Remote Workspace Technology Stipends, and Premium Corporate Health, Dental, Vision, and Wellness Benefits.