06/29/2025 updated
AS
100 % available
Machine Learning Engineer specializing in NLP and Computer Vision, Deep learning, LLM , RAG applicai
Lucknow, India
Only remote
Bachelor of Technology in Computer Science and Engineering (Specialization: DS and AI)C (Programming Language)Financial Data AnalysisArtificial Neural NetworksComputer VisionC++ (Programming Language)ForecastingPython (Programming Language)Machine LearningNLTK (NLP Analysis)NumPyPredictive ModellingVisualizationTensorFlowTime SeriesData Processing
Machine Learning & NLP
Development of NLP pipelines with NLTK and scikit-learn, implementing text vectorization techniques like TF-IDF, and building high-accuracy classification models achieving up to 98.43% accuracy with Random Forest.
Deep Learning & Computer Vision
Design of CNN architectures and implementation of transfer learning with ResNet-50 for image classification tasks, achieving 96%+ accuracy in crop disease detection across multiple plant species.
Data Processing & Analysis
Experience with data preprocessing, visualization, and analysis using Pandas, NumPy, and Matplotlib to uncover trends and patterns for model training and optimization.
Programming Languages
Proficiency in Python, C, and C++ for developing various machine learning applications and systems.
Deep Learning Frameworks
Implementation of neural network architectures using TensorFlow and Keras for time series prediction and computer vision tasks.
Model Optimization
Enhancement of computational efficiency through feature space tuning, reducing latency by up to 40% while maintaining model accuracy.
Time Series Analysis
Engineering of LSTM-based prediction models for financial data with effective preprocessing and visualization techniques.
Development of NLP pipelines with NLTK and scikit-learn, implementing text vectorization techniques like TF-IDF, and building high-accuracy classification models achieving up to 98.43% accuracy with Random Forest.
Deep Learning & Computer Vision
Design of CNN architectures and implementation of transfer learning with ResNet-50 for image classification tasks, achieving 96%+ accuracy in crop disease detection across multiple plant species.
Data Processing & Analysis
Experience with data preprocessing, visualization, and analysis using Pandas, NumPy, and Matplotlib to uncover trends and patterns for model training and optimization.
Programming Languages
Proficiency in Python, C, and C++ for developing various machine learning applications and systems.
Deep Learning Frameworks
Implementation of neural network architectures using TensorFlow and Keras for time series prediction and computer vision tasks.
Model Optimization
Enhancement of computational efficiency through feature space tuning, reducing latency by up to 40% while maintaining model accuracy.
Time Series Analysis
Engineering of LSTM-based prediction models for financial data with effective preprocessing and visualization techniques.
Experience
Professional experience0 - 5 years
Freelancer since2025
Languages
EnglishNative speaker
Project history
Pursuing Bachelor of Technology in Computer Science and Engineering with specialization in Data Science and AI. CGPA: 9.09/10
Engineered an LSTM-based stock price prediction model with Keras, achieving a test MSE of 16 on Netflix stock data.
Designed a deep learning system using CNN architectures and ResNet-50 transfer learning to detect crop diseases across nine plant species with 96%+ accuracy.