Intern- Technical Content

Job Description – Technical Content Intern [Applied AI]

Position Internship

Job Location-Mumbai

Qualification- B.Tech/M.Tech/BSc/MSc in CS, Data Science, Mathematics, or related field [Pursuing or recently graduated]

Duration -3-6 months (with an option to convert to permanent based on performance)

Stipend- 30,000 per month

Role Overview

upGrad is building AI-native learning experiences for millions of working professionals globally. As a Technical Content Intern, you will act as the crucial bridge between our Subject Matter Experts (SMEs) and our AI-driven video production pipeline. You will transform complex graduate-level AI concepts, from linear algebra to neural network optimization, into structured, visually coherent educational content. This is a hands-on role for someone who understands technical concepts and possesses the editorial rigor to teach them effectively.

Job Description

1. Scripting & Pre-Production

Review raw educational scripts provided by SMEs for language, flow, and technical accuracy. Translate these into Pre-Production Scripts (PPS), detailing precise visual descriptions and rendering cues for an AI video pipeline utilizing tools like Remotion, Manim, and HeyGen.

1. Quality Assurance & Feedback

Collaborate with the Content Lead to review AI-generated video previews, providing structured, actionable feedback to improve visual fidelity and instructional clarity before final rendering.

1. Live Session Development

Audit and refine live session learning materials. In cases where SMEs are strictly reviewers, you will independently draft presentation decks, Python code demonstrations, and applied lab assignments, iterating them based on SME feedback.

Skills required

• Solid conceptual foundation in machine learning mathematics (linear algebra, probability, calculus) and working knowledge of Python (NumPy, Pandas).
• Exceptional technical writing and editing skills; ability to identify logical gaps and simplify complex technical jargon without compromising epistemic accuracy.
• Strong visual content communication to map abstract mathematical concepts to concrete visual descriptions (e.g., deciding when a concept requires a 2D Cartesian plane versus a UI code-block layout).
• Ability to work independently, manage feedback cycles with technical experts, and communicate clearly.