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AI Engineer with less than a year in Agentic AI Systems and FastAPI development.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Gandham Ram Teja is an aspiring AI/ML Engineer with 3 months of internship experience in developing and integrating FastAPI tools for AI agents, particularly in customer service and appointment booking. Proficient in Python, Machine Learning, Deep Learning, and Natural Language Processing, he has worked on projects like federated fine-tuning of LLMs for psychological health analysis and building interactive job platforms with Python (FastAPI) and MySQL.
Sagi Ramakrishnam Raju Engineering College
B.Tech · Artificial Intelligence and Machine Learning
November 1, 2022 – April 29, 2026
Yanthraa Information Systems (YC-2021)
Artificial Intelligence and Machine Learning Intern
November 2, 2025 – December 30, 2025
Nidadavole, Andhra Pradesh, India
Federated Fine-Tuning of LLM for Physcological Health Analysis
January 18, 2026 – April 19, 2026
- Developed FedMental Care, a privacy-preserving mental health analysis system using Federated Learning and Large Language Models (LLMs) like RoBERTa. - Implemented LoRA-based parameter-efficient fine-tuning,reducing computational and communication over head while enabling distributed model training across multiple clients. - Trained on the Dreaddit dataset(190K Reddit posts) for stress detection,achieving 80% F1-score with minimal accuracy loss compared to centralized models while ensuring user data privacy
Voice-Based Appointment Booking Agent
November 16, 2025 – December 30, 2025
- Developed a voice-based agentic AI system using ElevenLabs that understands user intent and manages appointment booking through natural conversations. - Enabled the agent to autonomously check availability, book, reschedule, and cancel appointments using FastAPI tools exposed via API endpoints - Managed appointment data and booking history using PostgreSQL to ensure accurate scheduling and data consistency.
Cultural Fit Analysis
The candidate's projects demonstrate an interest in cutting-edge AI domains like Federated Learning and Agentic AI, indicating a proactive and innovative mindset. The academic background in AI/ML and multiple certifications suggest a strong drive for continuous learning and skill development. The diversity of projects (privacy-preserving LLMs, voice agents, job platform) shows adaptability and a broad technical curiosity. However, the limited professional experience makes it difficult to fully assess long-term cultural alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted AI systems, suggesting good problem-solving and project management skills. The focus on privacy-preserving AI and agentic systems aligns with modern operational needs for secure and autonomous solutions. However, the internship duration is very short, limiting the assessment of sustained operational fit and collaboration in a team setting.