About Me
I am a ML Engineer , currently working as an SDE at ITJOBXS. I have hands-on experience building end-to-end ML systems, designing Python-based ETL pipelines on GCP and Azure, and developing AI agents, RAG systems, and personalized chatbot solutions. I’ve also fine-tuned LLMs, improved product engagement through AI features. I enjoy building scalable, impactful solutions and collaborating across teams to turn ideas into real product value,and now I'm focused on ML infrastructure. I've been spending a lot of time lately with Spark and MLflow in production setups.
ExperienceSDE(ML)
ITJOBXS
• Developed and maintained scalable backend services using FastAPI and Django, building 10+ RESTful APIs that improved application performance, reliability, and reduced response times by 30%.
• Engineered and optimized responsive frontend applications using React.js, implementing reusable components and enhancing user experience, resulting in 25% faster page load times and improved usability.
• Designed and deployed AI-powered sales and marketing agents using LangGraph and LLM-based workflows, automating lead qualification and customer interactions, reducing manual effort by 50%.
•Built and orchestrated robust data pipelines using Apache Airflow, automating ETL workflows for large-scale datasets, improving data processing efficiency by 40% and ensuring reliable, scheduled data delivery.
• Engineered and optimized responsive frontend applications using React.js, implementing reusable components and enhancing user experience, resulting in 25% faster page load times and improved usability.
• Designed and deployed AI-powered sales and marketing agents using LangGraph and LLM-based workflows, automating lead qualification and customer interactions, reducing manual effort by 50%.
•Built and orchestrated robust data pipelines using Apache Airflow, automating ETL workflows for large-scale datasets, improving data processing efficiency by 40% and ensuring reliable, scheduled data delivery.
Consultant(Data Science)
Sep 15, 2024
UPGRAD
•Integrated AI-powered chatbots into the platform, significantly enhancing student engagement and support.
•Increased course-related doubt resolution by 70% through the deployment of LLM-based bots, improving learning outcomes and reducing response time.
• Fine-tuned multiple Large Language Models (LLMs) to cater to diverse use cases, including HR automation and academic query resolution, ensuring high accuracy and efficiency.
• Optimized AI models to enhance personalization, leading to a measurable improvement in user satisfaction and operational efficiency.
•Increased course-related doubt resolution by 70% through the deployment of LLM-based bots, improving learning outcomes and reducing response time.
• Fine-tuned multiple Large Language Models (LLMs) to cater to diverse use cases, including HR automation and academic query resolution, ensuring high accuracy and efficiency.
• Optimized AI models to enhance personalization, leading to a measurable improvement in user satisfaction and operational efficiency.
SkillsPython
Expert
Programming
SQL
Expert
Programming
Tensorflow
Advanced
Machine Learning
Pytorch
Advanced
Machine Learning
Java
Advanced
Programming
Apache Airflow
Advanced
Data Engineering
AWS
Advanced
Cloud
MLflow
Advanced
MLOPS
C++
Expert
Programming
Langchain
Advanced
Generative AI
LangSmith
Advanced
Generative AI
LangGraph
Advanced
Generative AI
LangFuse
Advanced
Generative AI
Qdrant
Advanced
Generative AI
FASTAPI
Expert
Programming
MongoDB
Advanced
Databases
Django
Expert
Programming
CUDA
Advanced
Generative AI
DOCKER
Advanced
MLOPS
Kubernetes
Advanced
MLOPS
vLLM
Advanced
Generative AI
Streamlit
Advanced
Programming
Gradio
Expert
Programming
Hugging Face
Expert
Generative AI
W&B
Advanced
Generative AI
SPARK
Advanced
Data Engineering
RAY
Advanced
Generative AI
Databricks
Advanced
Data Engineering
Snowflake
Advanced
Data Engineering
DBT
Advanced
Data Engineering
Kafka
Advanced
Data Engineering
Hadoop
Advanced
Data Engineering
Hive
Advanced
Data Engineering
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Languages
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ProjectsDEEP_RESEARCH_AGENT
Python
Docker
LangGraph
LangChain
github.com
A production-grade, multi-step AI research agent in Python that runs parallel live searches (Google, Bing, Reddit), scrapes and normalizes results via Bright Data, analyzes them with OpenAI/GPT, and returns a structured, cited synthesis — all orchestrated as a LangGraph workflow.
WEB_MASTER
Python
Docker
LangChain
Crawl4AI
Streamlit
github.com
AI tool to transforms any URL into a structured knowledge source by: extracting content using Crawl4AI ,vectorizing and summarizing data , running Retrieval-Augmented Generation (RAG) for deep information discovery, enabling a smart chatbot for interactive Q&A.
AI-Radiology-Reporting App
Python
Streamlit
PyTorch
LLM
github.com
AI-Radiology-Reporting app built using MAIRA-2 multimodal transformer designed for the generation of grounded or non-grounded radiology reports from chest X-rays.
Realtime_Data_Streaming_Pipeline
Python
Kafka
Spark
Zookeeper
Airflow
Cassandra
Docker
github.com
A real-time data streaming pipeline build using Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra—all neatly containerized using Docker.
KafkaStreamIQ-Real-Time-Stock-Market-Data-Pipeline
Python
Kafka
AWS
AWS Athena
AWS Glue
AWS EC2
github.com
KafkaStreamIQ is a real-world data engineering solution for ingesting, processing, and analyzing live stock market data. Leveraging Apache Kafka, Python, and AWS, this pipeline demonstrates a scalable, end-to-end architecture that transforms raw tick data into queryable insights.
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