Good. Now we switch mindset.
College placements ≠ Startup GenAI hiring.
For placements, recruiters care about:
- Strong fundamentals
- Clear internship
- 2–3 solid projects
- Achievements
- Clean formatting
- Not too “startup AI niche”
We make you look:
Strong Computer Engineering student with AI + backend exposure.
Not:
Hyper-niche GenAI infra engineer.
Below is your college placement optimized resume content.
This is clean, structured, safe for mass recruiters, product companies, and even service companies.
📄 COLLEGE PLACEMENT VERSION
SUMMARY
Computer Engineering student (PICT, 2027) with hands-on experience in backend development, AI systems, and performance optimization. Built scalable cloud-based pipelines and real-time applications using Python, FastAPI, AWS, and modern AI frameworks. Strong foundation in data structures, system design, and problem solving.
EDUCATION
Pune Institute of Computer Technology (PICT) — Pune
B.E. Computer Engineering | CGPA: 9.2 | 2023–2027
EXPERIENCE
AI Developer Intern – Across The Globe (Remote)
Aug 2025 – Present
- Contributed to backend components of an AI-driven educational content generation pipeline producing personalized multi-language video content.
- Optimized AWS Lambda execution time from ~20 minutes to ~14 minutes (~30% improvement), improving system efficiency and reducing compute cost.
- Developed internal automation tools including Markdown-to-PDF conversion and architecture diagram generation workflows.
- Assisted in building a document-grounded RAG system for answering internal queries and generating explanatory summaries.
PROJECTS
Nao Medical Translator
Python, FastAPI, WebSockets, Gemini, Whisper, React
- Built a real-time bilingual communication platform enabling live translation between doctor and patient using LLM-based translation and speech-to-text.
- Implemented WebSocket-based architecture for low-latency communication.
- Designed AI-based structured medical summary generation from consultation transcripts.
Intelligent Digital Asset Management System
Python, FastAPI, PostgreSQL
- Developed AI-driven image tagging and text-to-SQL search system enabling natural language queries on unstructured media data.
- Optimized database queries for efficient semantic retrieval across large datasets.
AI Architecture Diagram Generator
Python, LangChain, Rust
- Built automated system design diagram generator using structured LLM outputs.
- Reduced manual diagram creation effort through automated rendering workflows.
PUBLICATION
GNN-Based Friend Recommendation: A Graph Embedding Approach for Social Networks
Accepted for Conference Presentation
- Compared supervised MLP and retrieval-based friend recommendation systems.
- Demonstrated scalability benefits of ANN-indexed retrieval while maintaining competitive accuracy.
- Designed graph embedding workflows for large-scale social network datasets.
TECHNICAL SKILLS
Languages: Python, Rust, SQL, TypeScript, JavaScript
Frameworks: FastAPI, Flask, React, LangChain
Cloud & Tools: AWS (Lambda), Docker, Git, Linux
Concepts: Data Structures & Algorithms, OOPS, DBMS, Operating Systems, Computer Networks
🎯 Why This Version Is Placement-Friendly
- Balanced AI + fundamentals.
- Clean internship impact.
- Research paper boosts profile strongly.
- No over-niche GenAI marketing tone.
- Shows backend + cloud + AI exposure.
- Includes core CS subjects (important for placements).