AI Data Labeler

About the Role

The successful candidate will have a keen eye for detail and a strong understanding of data annotation principles. You will be responsible for labeling images and video frames with bounding boxes, polygons, segmentation masks, and SKU-level classifications, ensuring that the data is accurate and consistent.

Mashgin is a well-funded Series B startup that is already profitable, with a culture of extreme ownership, autonomy, and customer obsession. As a member of the team, you will have the opportunity to work on cutting-edge technology, collaborate with talented professionals, and see the direct impact of your work on the company's mission.

What You Will Do

• Label images and video frames with bounding boxes, polygons, segmentation masks, and SKU-level classifications
• Annotate edge cases, including occlusion, overlapping items, glare, motion blur, and unusual product orientations
• Maintain consistency against the labeling taxonomy and follow detailed annotation guidelines
• Tag training, validation, and test data to support model development and evaluation
• Compare model predictions to ground-truth labels and document failure modes
• Audit annotations from peers and contractors to enforce inter-annotator agreement
• Flag systemic issues such as recurring misclassifications, mislabeled SKUs, or low-quality captures
• Review confusion matrices and error reports with the ML team to prioritize fixes
• Identify capture issues that indicate hardware problems: blurry frames, poor lighting, color shifts, dropped frames, or camera misalignment
• Test devices in lab and field conditions to confirm image quality and end-to-end checkout accuracy
• Reproduce and document software bugs surfaced by labeling workflows or production telemetry

What We Are Looking For

• 2+ years of experience labeling data for computer vision, robotics, autonomous vehicles, or medical imaging
• Exceptional attention to detail and high tolerance for repetitive, precision-oriented work
• Experience with annotation tools such as CVAT, Labelbox, SuperAnnotate, Scale, or in-house tooling
• Comfort following detailed written guidelines and documenting ambiguous cases instead of guessing
• Strong written communication for clear, structured QA reports and Slack updates
• Comfort working with images and video from physical devices, and reasoning about visual edge cases
• Proficiency in Excel or other data analysis tools
• Strong analytical and problem-solving skills

Nice to Have

• Prior experience labeling data for computer vision, robotics, autonomous vehicles, or medical imaging
• Working knowledge of ML eval metrics and concepts
• Experience with data quality control and assurance
• Familiarity with Agile development methodologies

Benefits and Perks

• Opportunity to work on cutting-edge computer vision technology
• Collaborative and dynamic work environment
• Flexible working hours and remote work options
• Professional development and growth opportunities
• Access to the latest tools and technologies
• Comprehensive health insurance and benefits package
• Generous paid time off and holidays
• Stock options and equity participation

• Tip: Showcase your attention to detail by providing specific examples of your data annotation experience and how you ensured accuracy in your previous roles.
• Be prepared to discuss your experience with annotation tools and how you have used them to drive the development of computer vision models.
• Tip: Demonstrate your understanding of data quality control and assurance by describing your process for identifying and addressing errors or inconsistencies in datasets.
• Highlight your ability to communicate complex technical concepts effectively, both in writing and verbally.
• Tip: Research Mashgin's products and services to understand how your role as an AI Data Labeler contributes to the company's mission and goals.
• Be prepared to discuss your experience working with cross-functional teams and how you have collaborated with stakeholders to drive project success.