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Data Annotation Specialist (Machine Vision - Fruit Defects)
Optic Security Group
Hawke's Bay, NL, Canada
Posted on Mar 3, 2026
About Us
At Hawk Technology, we are dedicated to innovation and excellence in designing and manufacturing moulded fibre and post-harvest automated packing solutions. A key part of our Product Development programme is building advanced inspection and defect-sorting capability for apples and other produce. We’re seeking a detail-focused Data Annotation Specialist to help create high-quality training datasets that power our machine vision defect detection and grading systems.
Job Description
As a Data Annotation Specialist, you will be responsible for reviewing captured image/video data from our packing automation systems and accurately labelling fruit defects and relevant features. You will work closely with our Product Development Team (including machine vision/software engineers) to ensure annotation accuracy, consistency, and usability for model training and validation.
Key Responsibilities
Annotate and label fruit defects and quality attributes in image/video datasets using agreed standards and tools.
Review incoming data captures for quality (focus, lighting, angles, completeness) and provide feedback to improve capture processes.
Apply defect definitions consistently (e.g., bruising, russet, rot, scab, punctures, stem/calyx issues, blemishes) and escalate unclear edge cases.
Perform annotation QA (spot checks, audits, rework) to maintain dataset accuracy and consistency.
Assist with developing and maintaining defect taxonomies, annotation guidelines, and example libraries.
Work with engineers to clarify requirements for new defect categories, grading thresholds, and labelling formats.
Maintain clear documentation, including dataset versions, labelling notes, and summary reports.
Contribute to the continuous improvement of annotation workflows, tools, and productivity.
Skills / Abilities
Exceptional attention to detail and ability to follow standards precisely over repeated tasks.
Comfortable working with large volumes of visual data and maintaining consistent decisions.
Strong written communication for recording decisions, edge cases, and feedback to the team.
Practical understanding of fruit quality/defects (apple packhouse experience is a strong advantage).
Basic computer proficiency and confidence in learning new software tools (annotation platforms, spreadsheets, file systems).
Ability to manage priorities and meet deadlines while maintaining accuracy.
Experience with image annotation/QA tools (any platform) is an advantage.
Qualifications & Experience
Relevant experience in produce quality grading, packhouse operations, QA, horticulture, or data labelling/annotation preferred.
Experience working with apples (or similar produce) defect identification is highly regarded.
No specific degree required for the right candidate—training will be provided; demonstrated accuracy and reliability are essential.
Practical experience in a related field, including site/packhouse work, is an advantage.