Video Editing and Making Internship (Remote, Part Time) at Ritivel AI
Remote · Part Time internship
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- Stipend
- Stipend: INR 1,001 – INR 5,001 / month
- Duration
- 3 months
- Start
- Immediately
- Openings
- 20
Individuals able to commit to a work-from-home internship starting between September 4 and October 9, 2026, and available for a one-week period with relevant skills and interest in video editing and making. Women interested in starting or resuming their career are also welcome to apply.
- Work mode
- Work from home
- Resume
- Required to apply
About the internship
About the Internship
This internship at Ritivel AI offers a chance to develop and apply your video editing talents in a dynamic environment focused on creative AI developments. You'll work intricately with AI-generated videos to elevate their quality and appeal through editing and creative input.
Key Responsibilities
- Work alongside the research team to evaluate and enhance AI-produced video content.
- Provide constructive feedback on video edits and improve raw footage into refined, professional videos.
- Keep yourself informed of emerging trends and innovative practices in video editing and production.
- Support video shoots and assist the production team as needed.
Candidate Eligibility
Applicants must be able to work from home, start between September 4 and October 9, 2026, be available for a one-week duration, and possess pertinent skills and enthusiasm for video editing and production. The opportunity is also open to women aiming to launch or re-enter their careers.
Compensation and Benefits
The internship offers a weekly stipend ranging from ₹1,001 to ₹5,001, including a fixed pay of ₹1,000 to ₹5,000 plus a ₹1 incentive per week. Additional benefits include issuance of a certificate upon completion and flexible working hours to accommodate your schedule.
About the Company
Ritivel AI Private Limited specializes in the creation of advanced AI models focusing on creative tasks. Their work includes designing evaluation systems, developing reinforcement learning environments, and training models to reach state-of-the-art performance.