Data Annotation Reviewer (QA) — Egocentric Video

Workstream is a mission-driven company building the all-in-one HR, payroll, and hiring platform for managing the hourly workforce. 7 billion hourly workers, making up 80% of the global workforce, but this market has been heavily underserved by technology and deserves better. Workstream has been purpose-built for the hourly workforce from day one so that these businesses and their employees can thrive.

/Hardee's, IHOP, KFC, and Culvers. We are a high growth series B company and quickly expanding our product portfolio to deliver on our vision. We are backed by legendary VCs and industry experts like Founders Fund, BOND, and Coatue.

In addition to our core business, Workstream is home to a small, fast-moving Robotics team focused on advancing the next generation of artificial intelligence and robotics. We partner with a leading AI and robotics company to produce high-quality, large-scale egocentric (first-person) video datasets that help train advanced AI models. Our Robotics team develops scalable data collection and annotation pipelines that enable the efficient creation of high-quality training datasets, helping AI systems better understand human actions, environments, and everyday interactions.

We're also building a new category of connected hardware designed to operate reliably throughout the day in thousands of homes and businesses. By combining cutting-edge data collection, automation, and hardware innovation, this team is helping shape the future of intelligent systems and real-world AI applications. Grow With Us We produce high-quality training data for a leading AI/robotics client building a large-scale egocentric (first-person) video dataset.

Our pipeline auto-generates annotations at scale; your job is to review the segments flagged as potentially inaccurate , judge them against the client's guidelines, and correct or reject them so only clean data is delivered. This is precision quality-assurance work under a strict standard — audited batches must pass at a high accuracy threshold, and low-scoring batches are rejected outright. Your judgment directly affects whether our deliveries get accepted.

Day In The Life You will review: Language annotations — check that written descriptions and action labels accurately, clearly, and consistently describe what's happening in each video, following detailed labeling guidelines. Action segmentation timing — verify that videos are broken into correctly timed, non-overlapping action segments. Hand-pose tracking — sanity-check machine-generated hand and motion tracking, flagging errors and implausible results.

g. faces or personal information) and any content that doesn't meet collection quality or content standards. Quality standards Contribute to a high, continuously audited accuracy target — consistency matters as much as speed, since weak batches can be rejected as a whole.

Maintain alignment with other reviewers on shared calibration sets.

Who You Are

At least one year experience as a Data Annotation Reviewer Excellent written and reading English comprehension — you must accurately apply detailed, nuanced guidelines. This is the single most important requirement. Sharp attention to detail and the stamina for focused, cognitively demanding review.

Consistent, well-reasoned judgment on ambiguous, edge-case segments. Reliable high-speed internet and a device capable of smooth video playback. Comfort in a remote, target-driven environment with regular calibration checks.

Nice To Have

Prior data annotation, labeling, QA, or content-review experience. Familiarity with video annotation / labeling tools. Exposure to computer vision, robotics, or hand/gesture tracking concepts.