AI Engineer with less than a year in Machine Learning, Generative AI & LLM development.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Recently graduated B.Tech Artificial Intelligence and Machine Learning engineer (CGPA: 8.33) with 5 months of industry experience building production-ready machine learning systems, Generative AI applications, LLM pipelines, RAG architectures, and agentic AI workflows. Proficient in Python, TensorFlow, Scikit-learn, REST APIs, SQL, and MongoDB. Awarded Best Performer at Elevate Labs. Seeking a full-time role as an AI Engineer, Machine Learning Engineer, or Data Scientist.
Global Academy of Technology
B.Tech · Artificial Intelligence and Machine Learning
August 1, 2022 – June 30, 2026
Mahesh PU College
Pre-University · Physics, Mathematics, Chemistry, Computer Science
June 1, 2021 – May 31, 2022
FRND (Frnd-Interact Group)
AI Content Analyst Intern
January 1, 2026 – March 1, 2026
Bengaluru, Karnataka, India
Elevate Labs
Artificial Intelligence and Machine Learning Intern
September 1, 2025 – November 30, 2025
India
Freshness Tracker – Real-Time Deep Learning Pipeline
June 1, 2025 – August 31, 2025
Trained a Convolutional Neural Network (CNN) on 10,000 images, achieving 93% validation accuracy; improved performance by 11% via hyperparameter tuning and data augmentation. Engineered a real-time OpenCV inference pipeline with sub-100ms latency, validated for production via structured performance benchmarking.
Driver Drowsiness Detection – Agentic AI Safety System
January 1, 2025 – December 31, 2025
Built a production-ready agentic AI application combining MediaPipe, CNN classification, and Gemini AI LLM with RAG-style prompt engineering, orchestrating multi-source REST APIs into a real-time pipeline with sub-100ms latency. Deployed as a full-stack AI system applying MCP architecture principles and cloud-ready deployment practices.
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a passion for AI, particularly in safety systems and real-time applications. The internship experiences show adaptability to different roles within the AI domain (ML Intern, AI Content Analyst). The breadth of skills and tools used across projects and internships suggests a willingness to learn and apply diverse technologies, which aligns well with dynamic, innovation-driven environments. The focus on production-ready solutions indicates a practical, delivery-focused mindset.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experiences suggest strong problem-solving skills (root cause analysis, hyperparameter tuning) and a results-oriented approach (achieving 93% accuracy, sub-100ms latency). The 'Best Performer' award indicates a strong work ethic and ability to deliver. The experience as an AI Content Analyst Intern also points to attention to detail and structured feedback delivery, which are valuable for team collaboration and iterative development.