SHIVAM PATIDAR

AI Engineer

https://www.opentalent.in/shivam-patidar

AI Engineer with less than a year in Machine Learning, Deep Learning, and Cloud Platforms

Key Strengths

Strong academic background in Computer Science and Engineering with a focus on Big Data Analytics.
Demonstrated project experience in AI/ML domains, including CNN for weather prediction, Spark-based recommendation systems, and an AML system with RAG.
Proficiency in Python and relevant AI/ML libraries (TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, Pandas).
Familiarity with big data technologies like Spark, Hadoop, Kafka, and cloud platforms (AWS, Azure).
Certifications in AI Foundations, Generative AI Foundations, and Data Engineering from Oracle and AWS indicate a proactive learning approach.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate shows a strong interest in AI technologies and continuous learning, as evidenced by multiple certifications and academic projects. The diversity of projects (image classification, recommendation systems, fraud detection) indicates a broad interest in applying AI to different problem domains. The pursuit of a PG Diploma in Big Data Analytics further aligns with roles requiring robust data processing capabilities. However, all projects are academic, and there is no professional experience to assess cultural fit in a corporate setting.

Soft Skills & Operational Fit

The candidate's extracurricular activities, such as participating in a marathon and serving as a class representative, suggest teamwork, leadership, and communication skills. However, without direct work experience, the operational fit in a professional AI engineering environment, including stress handling and collaboration, is not explicitly demonstrated.

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About

Highly motivated and skilled individual pursuing a PG-Diploma in Big Data Analytics with a strong foundation in Python programming, data structures, and problem-solving. Possesses expertise in AI concepts, machine learning, deep learning, and cloud computing, demonstrated through certifications in AWS and Oracle. Proven ability to develop scalable solutions and implement complex algorithms, as showcased in projects involving weather prediction, music recommendation, and anti-money laundering systems. Eager to contribute to innovative engineering roles leveraging AI and data science skills.

Top Skills

PythonMachine LearningDeep LearningArtificial IntelligenceCloud Computing

Education

Centre for Development Advanced Computing

PG - Diploma · Big Data Analytics

August 1, 2025 – June 30, 2026

Acropolis Institute of Technology and Research

B.Tech · Computer Science and Engineering

August 1, 2020 – June 30, 2024

SVM High School

12th Grade

June 1, 2018 – May 31, 2020

SVM High School

10th Grade

June 1, 2016 – May 31, 2018

Projects

Anti-Money Laundering System (Ongoing)

January 1, 2026 – March 1, 2026

Built an AML system to detect suspicious transactions and financial fraud patterns in real-time banking environments. Applied rule-based detection and Isolation Forest for anomaly identification in high-volume financial transaction datasets. Integrated RAG pipeline for AML regulations and compliance policy retrieval with enhanced contextual intelligence. Automated explainable SAR report generation for regulatory compliance reporting and comprehensive audit readiness.

Music Recommendation System

September 1, 2025 – November 1, 2025

Built a scalable recommendation system using Spark and ML algorithms for highly personalized music recommendations. Implemented clustering and similarity-based filtering to significantly improve overall user recommendation precision rates. Processed large datasets efficiently using Hadoop HDFS and PySpark frameworks for scalable distributed data processing. Applied preprocessing, feature engineering, and evaluation techniques for improved overall system performance and accuracy.

Weather Prediction using CNN

April 1, 2025 – July 1, 2025

Built a weather image classification system using CNN, ResNet, and Inception architectures for accurate prediction. Implemented pooling, dropout, and batch normalization to improve overall model performance and reduce overfitting. Performed image preprocessing and data augmentation to enhance dataset quality and overall prediction accuracy. Evaluated models using K-fold cross-validation and standard classification metrics to ensure performance and accuracy.

Certifications

Certification of AWS for Generative AI Foundations

AWS

February 1, 2026 – Present

Certification of AWS for Data Engineering

AWS

January 1, 2026 – Present

Oracle Certified Foundations Associate AI Foundations

Oracle

October 1, 2025 – Present

Certification of AWS for Cloud Foundations

AWS

September 1, 2025 – Present

Certification of MPSSDEGB-FITT for AI Builder

MPSSDEGB-FITT

March 1, 2024 – Present

Certification of UDEMY for Python Programming

UDEMY

April 1, 2021 – Present

Key Strengths

Strong academic background in Computer Science and Engineering with a focus on Big Data Analytics.
Demonstrated project experience in AI/ML domains, including CNN for weather prediction, Spark-based recommendation systems, and an AML system with RAG.
Proficiency in Python and relevant AI/ML libraries (TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, Pandas).
Familiarity with big data technologies like Spark, Hadoop, Kafka, and cloud platforms (AWS, Azure).
Certifications in AI Foundations, Generative AI Foundations, and Data Engineering from Oracle and AWS indicate a proactive learning approach.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit