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AI & Machine Learning Engineer

Hi, I'm MOHD SHAMI

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Architecting, training, and deploying production-ready Machine Learning models, Deep Neural Networks, and NLP pipelines. Specialized in predictive intelligence, scalable inference APIs, and end-to-end MLOps solutions.

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Mohd Shami

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About Me

About Mohd Shami

AI & Machine Learning Engineer

Results-driven AI and Machine Learning Engineer with proven experience developing high-performance predictive algorithms, deep learning neural networks, and NLP systems. Proficient in PyTorch, TensorFlow, Scikit-learn, XGBoost, and Python. Skilled across the entire machine learning lifecycle: from exploratory data engineering and custom loss formulations to model evaluation and containerized API deployment.

I specialize in architecting intelligent systems that turn complex, high-dimensional datasets into automated decision engines. Combining strong foundational algorithmic problem-solving with cutting-edge AI methodologies, I build scalable, production-grade solutions for real-world business and clinical challenges.

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AI/ML Projects

0

Certifications

0

DSA Problems Solved

0

Internships

Location

Moradabad, UP, India

Education

B.Tech in Data Science & AI (Expected 2027)

Academic Rank

1st Rank in Academic Cohort (CGPA: 8.5/10)

Educational Journey

B.Tech in Data Science & Artificial Intelligence

Teerthanker Mahaveer University, Moradabad

Expected 2027

CGPA: 8.5/10 | 1st Rank in Academic Cohort | Specialized in Machine Learning & Neural Networks

Technical Expertise

AI & ML Proficiencies

Machine Learning & Deep Learning

Machine Learning (XGBoost, LightGBM, Scikit-learn) 96%
Deep Learning & Neural Networks (PyTorch, TensorFlow, CNNs) 90%
Natural Language Processing (NLP & Transformers) 88%
Statistical Modeling, Loss Optimization & Evaluation 92%

AI Engineering & MLOps

Python & Numerical Computing (NumPy, Pandas, SciPy) 98%
Model Serving & REST APIs (FastAPI, Flask, Docker) 90%
Feature Engineering & Data Pipelines (SQL, ETL) 94%
Experiment Tracking & Version Control (Git, CI/CD) 88%

AI/ML Frameworks & Technologies

Python
PyTorch
TensorFlow
Scikit-learn
Docker
FastAPI
Flask
SQL
Git
Pandas
NumPy
Matplotlib

Engineering Competencies

Algorithmic Thinking
System Architecture
Root Cause Analysis
Cross-functional Leadership
Technical Communication
Agile AI Prototyping
Engineering Experience

Industry Experience

Aug 2025 – Oct 2025

Machine Learning Engineer Intern

Codec Technologies India

  • Architected and tuned an XGBoost clinical disease classification model, boosting diagnostic validation accuracy from 72% to 85.4%
  • Engineered multi-stage automated feature extraction, outlier detection, and SMOTE imbalance-handling pipelines for high-dimensional tabular data
  • Implemented reproducible ML experiment tracking, cross-validation splits, and hyperparameter search grids using Scikit-learn and Python
  • Packaged trained model artifacts and built low-latency REST inference endpoints with comprehensive unit tests
XGBoost Python Scikit-learn Feature Engineering Git
Jun 2025 – Aug 2025

AI & Python Developer Intern

CodTech IT Solutions Pvt. Ltd.

  • Developed modular, high-throughput Python ETL pipelines (Pandas, NumPy) to process and cleanse heterogeneous data sources for model training
  • Automated data validation, metric reporting, and anomaly detection routines to ensure high-fidelity inputs for downstream AI workflows
  • Optimized vector arithmetic and batch data processing, reducing preprocessing latency by 40%
  • Authored clean API documentation and modular codebases adhering to PEP 8 standards and CI/CD best practices
Python Pandas NumPy ETL Pipelines Automated Testing
Featured ML Systems

AI & Machine Learning Projects

Revive - AI Clinical Risk Prediction

Revive - AI Clinical Risk Predictor

End-to-end intelligent diagnostic prediction system powered by optimized XGBoost with multi-factor risk attribution, improving clinical decision accuracy from 72% to 85.4% on patient health datasets.

XGBoost Python Scikit-learn Flask API
HamOrSpam NLP Classifier

HamOrSpam - NLP Text Classifier

High-precision NLP email filtering pipeline utilizing TF-IDF vectorization with n-gram feature extraction and SMOTE class rebalancing, delivering >98% accuracy and robust recall.

NLP TF-IDF SMOTE Scikit-learn
FarmAIQ Agricultural AI Suite

FarmAIQ - Smart Agricultural AI

Dual-model precision agriculture suite integrating a Random Forest soil-climate crop recommendation engine with a Deep CNN model in TensorFlow for crop disease classification.

TensorFlow CNNs Random Forest Python
Hands-On ML Experience

Interactive AI Lab

Test live interactive simulations of my Machine Learning models directly in your browser.

Input Patient Health Metrics

Diagnostic Risk & SHAP Impact

18% Low Risk
SHAP Feature Importance Attribution Latency: 2.1ms
Glucose Level+0.08
Blood Pressure+0.06
BMI Factor+0.04
Model Architecture XGBoost (85.4% Accuracy)
Primary Indicator Optimal Glucose & Blood Pressure
AI Diagnostic Recommendation Healthy parameters detected. Regular annual health checks advised.

Message Content

Try Presets:

Classification Result

HAM (Legitimate Message)
Spam Probability: 5% Model Confidence: 98.8%

Extracted TF-IDF Keyword Features

pipeline review python meeting

Soil & Climate Parameters

Recommended Crop

Rice

Optimal conditions detected for high-yield cereal crop cultivation.

Soil NPK Match 96%
Rainfall Index High

Neural Network Hyperparameters

Real-Time 2D Decision Boundary

Training Loss: 0.0342
Validation Acc: 97.5%
Epoch: 80 / 80
Loss Optimization Adam Optimizer (Adaptive Moment)
Convergence Status Optimal Decision Boundary Converged

Natural Language Text

Presets:

Multi-Class Emotion & Sentiment Matrix

Positive (94%)
Joy / Enthusiasm88%
Optimism / Confidence75%
Urgency / Alert12%
Frustration / Negative4%

Attention Weights / Significant Keyword Tokens

stunning (+0.92) thrilled (+0.89) accuracy (+0.65) ultra-low latency (+0.70)

Semantic Query Vector

Try Search Queries:

Top Semantic Search Matches (RAG Corpus)

Embedding Vector Dim 384 Dimensions (All-MiniLM-L6-v2)
Vector Search Index FAISS / HNSW (Hierarchical Navigable Small World)
Architecture & Engineering

ML Pipeline & Code Explorer

# Loading XGBoost Machine Learning Pipeline...
Terminal Execution Output

[SYSTEM] Environment initialized. Click "Run Code" to execute interactive python simulation.

Credentials & Specializations

Certifications & Credentials

Reliance Foundation

AI-Machine Learning Engineer

Comprehensive machine learning lifecycle, deep architectures, and production model serving.

2025 Verify
Simplilearn

Deep Learning Specialist

Neural networks, Convolutional Networks (CNNs), and transfer learning with PyTorch & TensorFlow.

2025 Verify
HackerRank

SQL (Advanced)

Complex query optimization, indexing, and high-performance data extraction for ML pipelines.

2026 Verify
HackerRank

Problem Solving (Intermediate)

Algorithmic efficiency, graph theory, dynamic programming, and data structures mastery.

2025 Verify
HackerRank

Python (Advanced Concepts)

Vectorized numerical operations, OOP, functional paradigms, and performance profiling.

2025 Verify
IBM

Data Science & AI Foundations

Statistical learning methods, predictive analytics, and enterprise data methodologies.

2026 Verify
Engineering Milestones

Key Achievements

AI Innovation

Smart India Hackathon

Led the AI engineering team with the "Revive" machine learning clinical prediction system, qualifying for the national selection round.

AI Team Lead 2025
Competitive Coding

850+ DSA Problems

Solved complex algorithmic challenges across LeetCode & HackerRank in Python, mastering tree/graph traversals, DP, and optimization.

Python Gold Badge
Technical Presentation

India AI Impact Summit

Presented applied machine learning research on gradient-boosted decision architectures for healthcare diagnostics to industry leaders.

Presenter National
Academic Excellence

1st Rank Academic

Consistently rank #1 in the B.Tech Data Science & AI cohort with a CGPA of 8.5/10 across all academic semesters.

TMU CGPA 8.5
Capabilities

AI & ML Services

End-to-End ML Systems

Designing custom machine learning models (XGBoost, LightGBM, Random Forest) with robust feature engineering and validation.

  • Predictive Modeling & Scoring
  • Automated Feature Pipelines
  • Hyperparameter Optimization

Deep Learning & NLP

Building convolutional networks (CNNs), text classification, NLP pipelines, and transformer-based semantic search systems.

  • Computer Vision CNNs
  • NLP & Sentiment Analysis
  • Neural Architecture Design

Model Deployment & MLOps

Deploying production-ready ML models as containerized REST APIs with FastAPI, Flask, and automated batch processing.

  • Low-Latency FastAPI / Flask Endpoints
  • Docker Containerization
  • Continuous Experiment Versioning
Client Reviews

What People Say

Dr. Rajesh Kumar

Dr. Rajesh Kumar

Senior Data Scientist, Codec Technologies

"Mohd demonstrated exceptional skills in machine learning model development. His XGBoost implementation improved our diagnostic accuracy significantly. A truly dedicated professional!"

Priya Sharma

Priya Sharma

Team Lead, CodTech IT Solutions

"Excellent Python developer with strong analytical skills. His ETL scripts improved our data pipeline efficiency tremendously. Highly recommended for data engineering roles!"

Amit Verma

Amit Verma

CTO, TechVision Analytics

"Outstanding work on our agriculture ML project. The crop recommendation system exceeded expectations. Great attention to detail and problem-solving abilities!"

Latest Articles

My Blogs

Sorting Algorithms Python
March 2025 8 min read

Classic Sorting & Searching Algorithms in Python

A deep dive into essential algorithms like Bubble Sort, Quick Sort, and Binary Search with Python implementations...

Read More
NumPy Matrix Operations NumPy
March 2025 6 min read

10 Powerful Matrix Operations in NumPy

Mastering linear algebra and matrix manipulations using the powerful NumPy library with practical examples...

Read More
Fake Internship Detector Machine Learning
March 2025 10 min read

Building a Fake Internship Detector

My journey of building an ML-powered detector to identify fraudulent internship postings using Streamlit and Scikit-learn...

Read More
Explore All Posts
Get In Touch

Contact Me

Let's Work Together!

I'm always interested in hearing about new projects and opportunities. Whether you have a question or just want to say hi, feel free to reach out!

Location

Moradabad, UP, India

Telegram

t.me/mohdshamii

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Get a comprehensive overview of my skills, experience, and achievements

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