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AI Engineer with less than a year in Machine Learning, Data Science & Web 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
Highly motivated AI/ML Engineer with experience in developing and deploying AI pipelines, real-time machine learning models, and multimodal AI assistants. Proficient in Python, SQL, C, JavaScript, and frameworks like FastAPI, React, and PyTorch. Demonstrated ability to achieve significant accuracy improvements and latency reductions in complex systems, with a strong focus on practical application and integration of AI solutions.
Ganpat University
B.Tech IT · Information Technology
August 1, 2022 – June 1, 2026
Shree S.V. Shah Vidhya Vihar
Higher Secondary · PCM
June 1, 2021 – March 1, 2022
BISAG-N
AI/ML Intern
January 1, 2026 – April 1, 2026
Gandhinagar, Gujarat, India
IBM SkillsBuild
AI Agent Architect Intern
June 1, 2025 – August 1, 2025
India
Bot Defender: Real-Time ML Traffic Classifier
June 8, 2026 – Present
Engineered real-time anomaly detection pipeline achieving sub-50ms inference latency; trained Random Forest on 200K+ logs from CIC-IDS-2017 dataset for binary bot classification. Architected PostgreSQL (Supabase) observability backend capturing traffic feature arrays, prediction outcomes, and confidence probabilities. Designed React model-monitoring dashboard to visualize real-time confidence scores, threat probabilities, and live network feeds.
Insurance Premium Prediction System
June 8, 2026 – Present
Benchmarked 5 regression models (Linear Regression, Decision Tree, Random Forest, XGBoost, Gradient Boosting) on 1,338 records × 7 features to identify the best-performing estimator. Achieved best R2 of 0.874 and RMSE of 4,425 with Gradient Boosting, outperforming baseline Linear Regression by 11.3% in R2. Deployed end-to-end prediction pipeline via FastAPI and containerized with Docker for portable, production-ready serving.
Data Science Foundation
Infosys SpringBoard
June 1, 2025 – Present
Data Analysis with Python
Cognitive Class.Ai
December 1, 2024 – Present
Crash Course on Python
Google, Coursera
November 1, 2024 – Present
Data Analytics & Visualization Job Simulation
Accenture
October 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from network anomaly detection to medical assistants and land-use change detection, indicates a broad interest in applying AI across different domains. Their involvement in both personal projects and internships, including a remote role, suggests adaptability. The target role of 'AI Engineer' aligns well with their demonstrated technical skills in ML model development, deployment, and system architecture. The breadth of technologies used (Python, FastAPI, Docker, React, PostgreSQL, MongoDB, PyTorch, Scikit-Learn) also points to a versatile and curious individual, which generally contributes positively to cultural fit in dynamic technical environments.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and problem-solving skills through their personal projects and internship contributions. Their ability to work independently and lead specific components within a team (BISAG-N) suggests good operational fit. The detailed descriptions of project outcomes (e.g., specific accuracy, latency, R2 scores) indicate a results-oriented mindset. However, without direct interview data, assessment of communication style, stress handling, and team collaboration remains limited.