Video Editing and Creation Internship (Remote, Part-Time)
Remote پارٹ ٹائم انٹرنشپ
درخواست دینے والے پہلے فرد بنیں۔
- وظیفہ
- Stipend: INR 22,000 – INR 60,000 / month
- دورانیہ
- 6 ماہ
- شروع کریں۔
- فوراً
- کھلنا
- 97
Candidates who can participate in a work-from-home internship, start between July 11, 2026, and August 15, 2026, are available for at least two weeks, and have the necessary video editing skill set and enthusiasm. Women reentering or beginning their careers are particularly welcome.
- کام کا موڈ
- گھر سے کام کریں۔
- دوبارہ شروع کریں۔
- درخواست دینے کی ضرورت ہے۔
انٹرنشپ کے بارے میں
Internship Overview
This internship involves engaging in video creation and editing tasks by utilizing high-quality Creative Commons assets. Responsibilities include producing videos, evaluating video content created by peers, and sourcing appropriate video materials.
Eligibility Criteria
- The candidate must be available for a remote internship.
- The internship start date should be between July 11, 2026, and August 15, 2026.
- Applicants must be able to commit to a 2-week internship duration.
- Possessing relevant video editing skills and interests is essential.
- Women aiming to commence or return to their professional career are also encouraged to apply.
Compensation
The stipend ranges between 22,000 and 60,000 INR monthly. The total stipend structure includes a fixed monthly pay between 2,000 and 20,000 INR, along with performance-based incentives from 20,000 to 40,000 INR.
Perks
- Flexible working hours to accommodate personal schedules.
- Certificate of completion upon internship conclusion.
About Parsewave
Parsewave specializes in developing customized datasets, expert feedback, trace solutions, and quality-controlled training data for cutting-edge AI applications. Their expertise lies in creating refined, private, evaluation-focused datasets that facilitate enhancements in AI reasoning, coding, and autonomous capabilities. The company operates at the data quality level crucial for AI evolution, dealing with requirements analysis, dataset architecture, custom problem development, multilayer quality assurance, and iterative improvements based on model outputs. Parsewave's solutions support supervised fine-tuning, reinforcement learning through human feedback, and benchmarking of AI models.