Vishal Sharma
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in Machine Learning & Python Development
Highly motivated and results-oriented AI Engineer Intern with hands-on experience in Machine Learning, Computer Vision, and natural language processing. Proficient in Python, FastAPI, and various AI/ML frameworks. Adept at developing scalable solutions, optimizing system performance, and integrating advanced AI models into practical applications, as demonstrated through projects like the Conversational AI Calendar Booking Agent and Urban Air Quality Toolkit. Strong problem-solving and communication skills with a foundational understanding of cloud platforms like Azure and AWS.
The NorthCap University
B.Tech CSE · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Doon Public School
Class XII (CBSE)
June 1, 2020 – May 31, 2021
Doon Public School
Class X (CBSE)
June 1, 2018 – May 31, 2019
Unique Training Solutions
Trainee
October 1, 2024 – November 1, 2024
India
Octanet Pvt. Ltd.
Intern
May 1, 2024 – June 1, 2024
India
WorkGuardAI – Excavation Monitoring (CV & ML)
November 1, 2025 – Present
• Trained a YOLOv8 computer vision model for real-time PPE and safety violation detection. • Structured cloud-native detection telemetry capturing image-level bounding box data, class confidence scores, and violation metadata per inference frame. • Deployed REST API endpoints using FastAPI for real-time inference and integrated cloud-native telemetry pipelines.
Hybrid Deep Learning for Stock Trend Reversal
November 1, 2025 – Present
• Trained CNN models for pattern detection in financial time-series data. • Applied feature engineering, data preprocessing, and model evaluation techniques to build a hybrid CNN-LSTM ensemble for financial time-series forecasting.
Conversational AI Calendar Booking Agent
July 1, 2025 – Present
Built a conversational AI agent using FastAPI, LangGraph, and Streamlit to schedule meetings on Google Calendar via natural language input. • Integrated Google Calendar API for real-time appointment booking and retrieval. • Enabled smooth user interaction through a Streamlit frontend with intent recognition and slot filling. • Implemented LangGraph-based agentic workflows with multi-step reasoning, tool calling, and intent recognition for autonomous meeting scheduling using LLM APIs.
Urban Air Quality Toolkit
May 1, 2024 – July 1, 2024
Developed an interactive toolkit for detecting urban pollution hotspots using crowdsourced data, real-time path analysis, and Tableau visualizations.
AWS Academy Data Engineering
AWS
June 1, 2026 – Present
Java Beginner To Master
Udemy
June 1, 2026 – Present
Microsoft Azure AI Fundamentals 900
Microsoft
October 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from urban air quality to conversational AI and computer vision for safety, indicates a broad interest in applying AI across different domains. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus. The candidate is currently pursuing a B.Tech, indicating a strong academic background and a proactive approach to learning new technologies, as evidenced by multiple certifications. However, the experience is primarily academic and internship-based, which might require mentorship in a fast-paced industry setting.
Soft Skills & Operational Fit
The candidate's resume highlights 'Problem-Solving' and 'Communication Skills' as additional skills. Project descriptions indicate an ability to work on complex problems and articulate technical solutions. The academic nature of most projects suggests a learning-oriented individual, but direct experience in a professional, collaborative operational environment is limited. The 'ATM model in Python using OOP' project mentions optimizing system performance, which hints at an operational mindset, but further validation is needed.