Robotics Data Annotator

About the Role

Before you start, read the step-by-step guide. It walks through the whole process with screenshots, including exactly what your final screenshot needs to show. An unclear or incomplete final screenshot is the one thing that will stop your application, so it is worth ten minutes before you begin.

Sovrano places annotators on robotics data projects for AI companies building the next generation of robot learning models. The work is describing what a robot or a human hand is doing in short video clips, frame by frame or as a caption. Things like twisting left, loosening a bolt, gripping a handle. Precision and consistency matter far more than speed or creativity.

Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

You complete a free qualification now, on our partner's annotation platform. Projects open with little notice, which is why we qualify people in advance rather than scrambling when one lands.

The qualification is an English check, a typing check, optional practice tasks, and a 5-task exam. It is free, you do it in your own time, and nobody pays anything at any point.

One rule matters more than the rest: sign up on the partner platform using the same email address you apply with here. That is how we confirm your result. A different address means we cannot verify that you passed.

Finishing the exam is not the last step. Once it is done, come back and complete the short completion form we link in your application email. It asks for the email address on your platform account, the referral code you used, and a screenshot of your completed exam. We cannot verify you without it, so your application is only complete once that form is in.

Key Responsibilities

• Describe robotic and manual actions in short video clips, frame by frame or by caption

• Apply the project label guide consistently across every task, not just the first ten

• Keep accuracy high across a full working session

• Flag unclear, corrupted or low quality clips instead of guessing

• Meet the agreed turnaround once you are allocated to a project

• Raise questions early when a clip does not fit the guide

Ideal Qualifications

• Working English, both reading and writing

• Comfortable following a written label guide precisely and repeatedly

• A laptop or desktop computer and a reliable internet connection

• Able to work independently, remotely, without supervision

• Able to set up two factor authentication on your phone

• Available for at least a few hours a week when a project opens

Nice to Have

• Previous annotation, labelling or data QA experience

• Exposure to robotics, video annotation or computer vision datasets

• Fast and accurate typing

• Availability at short notice when a project opens

• Experience working to a written spec in a remote team

What Success Looks Like

• You pass the qualifying exam and enter our qualified pool

• Your annotations need little or no rework when reviewed

• You stay consistent across a full session, not just the first few tasks

• You raise ambiguity instead of guessing

• You are someone we can place on the next project without retraining

Contract & Payment Terms

Freelance, project based, fully remote.

The qualification is free and unpaid. When you are allocated to a project, you are paid hourly at a rate between $5 and $15 per hour, set by your experience and your assessed accuracy, and confirmed to you in writing before any work starts. Payment is monthly against approved hours.

Hours vary by project and are agreed with you before you begin. This posting is a pre-qualification for upcoming projects. It does not guarantee an offer of work or any specific number of hours.