About Arctic Engine:
Arctic Engines is an enterprise-grade Al human data operations company specializing in high-quality training data, RLHF, and human feedback pipelines for frontier Al models. We are part of the Apna Group, one of India's fastest-growing unicorns, backed by marquee investors such as Lightspeed, Tiger Global, Insight Partners, Peak XV, and others. With native access to Apna's 60M+ workforce, we deliver high-quality training data at unmatched scale and speed.

Company:
Arctic Engines

Requirement:
1

Location:
Bengaluru (Work from office - Domlur | 6 days)

Employment:
Full time

Experience:
3+ years in video annotation quality assurance, including team leadership

Joining:
Immediate joiners preferred

Requirement: 1

CTC:

About The Role
We are looking for a
QC Lead
to own annotation quality for egocentric industrial video datasets. You will define review standards, lead the QC team, identify recurring errors, and ensure that delivered annotations meet project requirements.

Requirements
Responsibilities




Lead reviewers and establish calibration, review, feedback, and rework processes
Audit video chunking, temporal action boundaries, keypoint annotations, action labels, and natural language descriptions
Check timestamp accuracy, coverage, label consistency, and the correctness of descriptions against the video
Define QC checklists and sampling plans; track error rates, reviewer agreement, rejection trends, and quality improvements
Resolve ambiguous cases, update guidelines, and coach annotators and reviewers
Validate structured outputs and work with tooling teams to address workflow or export issues

Requirements
Direct experience with industrial video, robotics, or Physical AI datasets is mandatory.\
Hands-on expertise in egocentric video annotation, temporal action segmentation, keypoint annotation, action taxonomies, and timestamped descriptions
Experience leading annotation QC teams and creating transparent guidelines and calibrat

📌 Qc Lead Bengaluru (India)
🏢 apna
📍 India