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Machine Learning Engineer Data Scientist

Transforming Data into Intelligence Through Advanced ML Solutions

About Me

Who I Am

A passionate Machine Learning Engineer with expertise in developing and deploying scalable AI solutions. With 5+ years of experience in the field, I specialize in deep learning, computer vision, and natural language processing.

What I Do

I transform complex data challenges into intelligent solutions, helping organizations leverage the power of AI to drive innovation and efficiency.

Deep Learning
Computer Vision
NLP
MLOps

Technical Expertise

Machine Learning 95%
Deep Learning 90%
Data Science 85%
MLOps 80%

Areas of Expertise

Deep Learning

  • • Neural Networks Architecture
  • • CNN & RNN Implementation
  • • Transfer Learning
  • • Model Optimization

Computer Vision

  • • Object Detection
  • • Image Segmentation
  • • Face Recognition
  • • Video Analysis

NLP

  • • Text Classification
  • • Sentiment Analysis
  • • Language Generation
  • • Named Entity Recognition

MLOps

  • • Model Deployment
  • • Pipeline Automation
  • • Version Control
  • • Monitoring & Maintenance

Data Engineering

  • • ETL Pipelines
  • • Data Warehousing
  • • Big Data Processing
  • • Data Quality Assurance

R&D

  • • Algorithm Development
  • • Research Papers
  • • Proof of Concepts
  • • Innovation Projects

Featured Projects

Image Recognition System

Deep learning-based image recognition system with 98% accuracy on custom datasets.

PyTorch CNN Computer Vision

NLP Chatbot Platform

Advanced conversational AI system with contextual understanding and multi-language support.

Transformer BERT NLP

Predictive Analytics Engine

Time series forecasting system for business metrics with anomaly detection.

TensorFlow Time Series MLOps

Research Publications

Advanced Neural Network Architectures for Real-time Object Detection

Published in International Journal of Computer Vision, 2023

A novel approach to improving object detection accuracy while maintaining real-time performance through innovative neural network architectures.

Deep Learning Computer Vision Real-time Systems

Transformer-based Approaches to Multi-modal Learning

Published in Conference on Machine Learning (ICML), 2022

Investigating the effectiveness of transformer architectures in combining visual and textual data for enhanced learning outcomes.

Transformers Multi-modal NLP

Education & Certifications

Ph.D. in Machine Learning

Stanford University

2018 - 2022

Research Focus: Deep Learning Architectures

Thesis: Advanced Neural Networks for Computer Vision

M.S. in Computer Science

MIT

2016 - 2018

Specialization: Artificial Intelligence

GPA: 3.95/4.0

B.Tech in Computer Science

IIT Delhi

2012 - 2016

Major: Computer Science & Engineering

GPA: 9.8/10.0

Professional Certifications

Google TensorFlow Certificate

Google • 2023

AWS Machine Learning Specialty

Amazon Web Services • 2022

Deep Learning Specialization

Coursera • 2021

Professional Experience

Google AI

Senior ML Engineer

2021 - Present

TensorFlow PyTorch MLOps

Led a team of 8 engineers in developing and deploying large-scale machine learning systems.

  • Architected and implemented a real-time recommendation system serving 1M+ users
  • Improved model inference time by 40% through optimization techniques
  • Developed MLOps pipeline reducing deployment time by 60%
  • Published 3 research papers in top-tier conferences

Microsoft Research

ML Research Engineer

2019 - 2021

Deep Learning NLP Azure ML

Conducted cutting-edge research in natural language processing and computer vision.

  • Developed novel transformer architecture improving BERT performance by 15%
  • Created efficient training methods for large language models
  • Filed 2 patents for innovative ML techniques
  • Mentored junior researchers and interns

Amazon AWS

ML Engineer

2017 - 2019

AWS SageMaker Computer Vision Python

Built and deployed machine learning solutions for AWS customers.

  • Implemented computer vision models for retail analytics
  • Developed automated ML pipeline reducing training time by 50%
  • Created documentation and tutorials for AWS ML services
  • Collaborated with product teams to improve AWS SageMaker features

Latest Blog Posts

Deep Learning 5 min read

The Future of Transformer Architecture in 2024

Exploring the latest advancements in transformer models and their impact on AI applications.

Posted on

Jan 15, 2024

Read More
MLOps 8 min read

Building Scalable ML Infrastructure

Best practices for designing and implementing production-ready ML systems.

Posted on

Jan 10, 2024

Read More
AI Ethics 6 min read

Ethical Considerations in AI Development

Addressing the key challenges and responsibilities in modern AI development.

Posted on

Jan 5, 2024

Read More

Get In Touch

Contact Information

Location

San Francisco, CA

Available Hours

9:00 AM - 6:00 PM PST

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