Jobgether
Video Annotation & Data Labeling Specialist

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Video Annotation & Data Labeling Specialist
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Video Annotation & Data Labeling Specialist based in United Kingdom.
This role offers the opportunity to contribute directly to the development and improvement of next-generation AI models through high-quality video data annotation.
You will analyze video content, segment sequences, label observable actions, and verify AI-generated descriptions for accuracy.
No previous professional experience is required, making this an accessible opportunity for candidates who are detail-oriented and eager to learn.
You will receive structured training and certification before progressing to paid production work.
Consistent, high-quality performance can provide priority access to more advanced and higher-paid AI data projects.
The role is designed for reliable contributors who can follow precise guidelines and maintain strong accuracy across large volumes of annotation tasks.
Accountabilities
- Write objective, concise 1–2 sentence summaries of video sequences using simple and accurate English.
- Segment videos into clearly defined, action-based sequences without gaps or overlaps.
- Label and describe only actions that are directly and visually verifiable in the video.
- Use simple present tense and consistent terminology when creating annotations.
- Review AI-generated captions and identify or correct inaccuracies, inconsistencies, and unclear descriptions.
- Follow project-specific annotation guidelines precisely to ensure consistency across datasets.
- Maintain a high level of accuracy and productivity while completing assigned annotation batches.
- Complete the required onboarding and certification activities, including reviewing guidelines, practicing with the annotation platform, and successfully completing five certification tasks.
- Apply feedback from quality reviews to continuously improve annotation accuracy and consistency.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- No previous professional experience in data annotation or AI is required; beginners are welcome.
- Strong attention to detail and the ability to identify specific actions and events in video content.
- Ability to describe only what is visibly observable without making assumptions, interpretations, or unsupported conclusions.
- Strong written English skills with the ability to produce clear, concise, and objective descriptions.
- Ability to consistently follow detailed instructions, annotation guidelines, and quality standards.
- Commitment to maintaining a target benchmark of 95%+ accuracy.
- Strong organizational skills and the ability to manage repetitive tasks while maintaining accuracy and focus.
- Ability to learn new annotation tools and workflows quickly.
- Reliable availability for 25–40 hours per week for long-term data annotation projects.
- Willingness to complete an approximately 3-hour certification and onboarding process before entering paid production work.
Benefits
- Compensation of $2.00–$5.00, depending on verified quality and productivity.
- 25–40 hours per week of dedicated, long-term data annotation opportunities.
- No prior professional experience required, with beginners encouraged to apply.
- Structured onboarding, training materials, and practical experience with an annotation platform.
- Certification process designed to prepare contributors for paid production work.
- All certification hours are paid once you begin performing production tasks.
- Priority access to advanced and higher-paid projects based on successful performance.
- Opportunity to gain practical experience contributing to AI model development and verification.
- Long-term project opportunities for consistent, high-quality contributors.


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How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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