Project Rana - Human Pose Keypoint Annotation QC (Thermal Imagery)

Welo Global; India; Remote; INR 400,000 - 650,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Global community support

Job summary

Welo Data is seeking a detail-oriented QC Reviewer to ensure accuracy of human pose keypoint annotations on thermal images. You will review annotator submissions in Label Studio, verify keypoint placements, and provide feedback to drive rework where needed.

With strong attention to detail, you will assess inferred keypoints for plausibility and ensure confidence flags are applied correctly. This role is fully remote within India and offers flexible project-based opportunities.

Qualifications

• Experience in computer vision annotation QA or related quality-control role.
• Strong understanding of human anatomy and pose structure for keypoint placement.

Responsibilities

• Review keypoint annotations against source thermal images for person count and per-person completeness.
• Verify each keypoint is placed near the anatomical center of the body part.
• Assess inferred keypoints for plausibility and consistency with visible pose.
• Check confidence flags for uncertain cases and flag misused indicators.
• Provide actionable feedback within Label Studio review workflow.

Skills

Annotation QA

Attention to detail

Technical comprehension

Written communication

Tools

Label Studio

Job description

About the Role

We are looking for a detail-oriented QC Reviewer to ensure the accuracy and consistency of human pose keypoint annotations on thermal images. You will review annotator submissions within Label Studio, verify correct keypoint placement (including inferred positions for occluded body parts), and provide clear feedback to drive rework where needed.

Key Responsibilities

• Review completed keypoint annotations against the source thermal images, verifying person count and per-person annotation completeness.
• Check that each keypoint is placed as close as possible to the true anatomical center of the corresponding body part.
• Evaluate whether inferred keypoints (for occluded/obstructed body parts) are anatomically plausible and consistent with visible body positioning.
• Verify that confidence flags were applied appropriately for uncertain or difficult cases, and flag missing or misused confidence indicators.
• Identify systematic errors or patterns of confusion (e.g., consistent mislabeling in certain poses or occlusion types) and report them for annotator calibration.
• Provide specific, actionable feedback on rejected or revised annotations within Label Studio's review workflow.
• Participate in periodic calibration sessions to align QC standards with the client's evolving guidelines or edge-case resolutions.
• Track and document review outcomes, common error types, and annotator performance trends as required.

Requirements Required:

• Prior experience in computer vision annotation QA, review, or a related quality-control role.
• Strong understanding of human anatomy and pose structure to accurately assess keypoint placement, including inferred/occluded cases.
• Exceptional attention to detail — able to catch subtle placement errors, incorrect inferences, or misapplied confidence flags.
• Comfort working with thermal/infrared imagery and its visual limitations.
• Ability to apply detailed annotation/QC guidelines consistently and exercise sound judgment on ambiguous or edge-case scenarios.
• Strong written communication skills for providing clear, constructive feedback to annotators.
• Familiarity with Label Studio, including review/approval workflows, or willingness to quickly learn the platform.
• Reliable, self-directed work habits with the ability to meet review turnaround expectations.

Nice to Have:

• Direct experience with human pose estimation datasets (e.g., COCO keypoints) or keypoint QA specifically.
• Experience with thermal/infrared imagery QA.
• Background in computer vision, robotics, or security/surveillance imaging.
• Experience managing structured QA/rework feedback loops for annotation teams.

Why Join Welo Data?

• Limitless Flexibility Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
• Limitless Growth Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
• Limitless Support Be part of a global contributor community with responsive guidance and support.
• Real Impact Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.

About Welo Data

Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries. At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.