Computer Vision Annotation Associate

HRCap, Inc.; United States; Remote; USD 52,000 - 68,000; Full time

Benefits offered by this job

Remote workspace stipend

Health benefits

Wellness benefits

Job summary

HRCap, Inc. is seeking an entry-level Computer Vision Annotation Associate to join our fully distributed Data Operations division.

You will label high-quality ground truth datasets for training neural networks and deep learning models. Responsibilities include annotating images/videos with 2D/3D boxes, polygons, and segmentation, performing QA to reach 99% accuracy, and collaborating with ML engineers to refine labeling taxonomies.

Qualifications

• Bachelor’s degree in a relevant technical or quantitative discipline.
• 0–2 years of professional experience; internships valued.
• Strong visual pattern recognition and high attention to detail.
• Comfort working in a distributed remote team.

Responsibilities

• Label and annotate visual datasets with bounding boxes, polygons, polylines, keypoints, and segmentation masks.
• Conduct QA checks on pre-labeled data to maintain 99%+ accuracy.
• Collaborate with ML engineers to refine labeling taxonomies and report edge cases.
• Use cloud-based annotation tools and provide UX feedback to speed up processing.
• Document and track workflow metrics and project backlogs in Jira or spreadsheets.

Skills

Data annotation

Quality assurance

Remote independence

Attention to detail

Education

Bachelor’s degree in CS/DS/IT/math/cognitive science or equivalent

Tools

CVAT

LabelImg

Labelbox

Roboflow

Job description

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 Associateto 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.
• 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.