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. There are 2.7 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.

Our customers include leading brands from multiple sectors, including Burger King, Carl's Jr./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.

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. Compliance — flag privacy issues (e.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. Meet the throughput target

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. Know More About Workstream

https://www.workstream.us/blog/funding-series-b https://techcrunch.com/2021/08/26/workstreams-text-based-recruitment-tool-gets-a-48m-bet-from-bond-and-beyond/ https://techbuzz.news/buzzworthy-august-27-2021/

Additional Information

Workstream provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

We are committed to the full inclusion of all qualified individuals.