Dec 2023 – Present · 2 yrs 3 mos

• Leading the development of cutting-edge AI products and driving innovation in the E-commerce sector. Passionate about crafting solutions that redefine user experiences and elevate business success. #AI #Ecommerce #Innovation #TechLeadership

Jan 2023 – Jan 2024 · 1 yr

• 1) Exploring GANs (Generative Adversarial Networks) network for various applications.
• 2) Engaging in computer vision tasks to enhance image and video analysis.
• 3) Utilizing GPU compute resources for optimized inference, with a focus on AWS and GCP environments.
• 4) Developing backend services using technologies such as FastAPI, Python-ODM (Pydantic, Beanie), Uvicorn, REST API design, MongoDB (NoSQL database with optimized query strategies), AWS Lambda functions, CloudWatch, API Gateway, and Mangum.
• 5) Front-end development using React JS, JavaScript, HTML, and CSS to create user-friendly web interfaces.
• 6) Implementing Docker-based deployment, including containerized databases and network setups, within Kubernetes (K8s) for efficient and scalable application deployment.
• In conclusion, the ongoing efforts involve developing a robust and scalable dashboard backend using FastAPI, Beanie ODM, Motor, FastCache2, Docker, and Uvicorn, which results in exceptional performance and responsiveness for the system.
• Leading the development of cutting-edge AI products and driving innovation in the E-commerce sector. Passionate about crafting solutions that redefine user experiences and elevate business success. #AI #Ecommerce #Innovation #TechLeadership

Dec 2022 – Jan 2023 · 1 mo · Toronto, Ontario, Canada · Remote

• 1) Utilized Hugging Face models for various natural language processing tasks.
• 2) Fine-tuned BERT models for question answering using pre-trained weights to improve accuracy.
• 3) Engaged in data preparation, ensuring high-quality and well-structured datasets for machine learning projects.
• 4) Implemented Elasticsearch, including CRUD (Create, Read, Update, Delete) API operations and text search features, enhancing data retrieval and management capabilities.

Sep 2022 – Feb 2025 · 2 yrs 5 mos · Marietta, Georgia, United States · Remote

• 1) Audio Classification and Speech Recognition: Focused on understanding and classifying audio data, alongside feature engineering for signal processing.
• 2) Activity Recognition: Developed models to identify and classify different activities from 2D image data, with a focus on feature engineering techniques.
• 3) Advanced Audio Analysis: Employed the YAMNet architecture, utilized transfer learning techniques, fine-tuned models, incorporated LSTM layers, and applied Short-Time Fourier Transform (STFT) and Mel Spectrogram feature engineering to enhance audio analysis and recognition capabilities.

Apr 2022 – Jan 2023 · 9 mos · Bengaluru, Karnataka, India · On-site

• 1) Worked on computer vision problems using CV2, PyTorch, TensorFlow, Keras, Python, and CUDA-GPU.
• 2) Deployed applications to the cloud using AWS, Flask API, Elasticsearch, and MongoDB.
• 3) Explored state-of-the-art techniques for object detection and MOT (Multiple Object Tracking).
• 4) Addressed video analytics problems using PyTorch, Keras, and CV2.
• 5) Dockerized various AI and backend applications for deployment.
• 6) Deployed AI models on Nvidia GPUs and OpenVino CPUs for edge AI.
• 7) Implemented Apache Kafka for real-time data-stream processing and notification alerts with IoT devices for critical situations.
• 8) Developed scalable backends using Flask, Apache, Nginx, Redis for cache management, Celery for task management, and No-SQL databases like MongoDB and Elasticsearch.
• 9) Deployed scalable edge analytics solutions using K3S for vision-based applications, Redis-Ai, and Redis Stream Service.
• 10) Deployed applications on Kubernetes (K8S) across various cloud platforms.

Jun 2020 – May 2022 · 1 yr 11 mos · Bengaluru, Karnataka, India

• 1) Primarily focused on computer vision tasks, specifically detection and segmentation.
• 2) Optimized the Object Detection Model using pruning and quantization methods.
• 3) Responsible for server deployment on AWS and Flask Apache.
• 4) Implemented NLP cosine similarity search using Elasticsearch.
• 5) Managed CRUD operations for MongoDB and Elasticsearch.
• 6) Excelled in writing efficient queries for Elasticsearch and MongoDB.
• 7) Utilized text data for fault detection.
• 8) Deployed machine learning models on Flask.
• 9) Prepared datasets for detection and segmentation problems.
• 10) Managed GCP and Azure VMs as part of cloud administration tasks.
• 11) Developed APIs using Flask and AWS services such as Lambda functions, API Gateway, and S3 buckets.
• 12) Documented the proof of concept (POC) projects in NLP and computer vision.
• 13) Administered Git for various projects.
• 14) Conducted both manual testing and automation testing using Python, including unit tests.
• 15) Set up and configured Jenkins for automation testing and deployment to stage and production servers.

Jan 2020 – Jun 2020 · 5 mos · Greater Bengaluru Area

• 1) Worked on image processing Method.
• 2) Conducted object detection for autonomous vehicles.
• 3) Implemented image semantic segmentation using UNet and other techniques.
• 4) Utilized semi-annotation tools for identifying objects in images.
• 5) Performed model optimization and hyperparameter tuning for various deep learning state-of-the-art techniques, such as segmentation and detection.
• 6) Worked on various models of Yolo and segmentation (different types of segmentation).
• 7) Utilized Python, CV2, PyTorch, and Keras for tools and technologies.

Sep 2019 – Dec 2019 · 3 mos · Greater Bengaluru Area

• 1) Data Annotation for Object Detection, specifically in YOLO format, to assist in training object detection models.
• 2) Data Annotation for Segmentation, including instance segmentation and segmentation in UNet format, contributing to image segmentation model training.
• 3) Mask Generation for Segmentation Problems, involving the creation of masks to facilitate segmentation tasks.
• 4) Extensive work in image processing, encompassing tasks such as image cleaning, video stabilization, dehazing, color toning, exposure toning, gamma correction, utilizing techniques like SIFT (Scale-Invariant Feature Transform), optical flow analysis, contour detection, and more.

Jun 2019 – Aug 2019 · 2 mos · Greater Delhi Area

• 1) Conducted political analysis using machine learning with Python.
• 2) Studied the Greater Kailash constituency in New Delhi to identify interesting voting trends in its booths.
• 3) Extracted data from the 2008, 2009, 2013, 2014, and 2015 elections and converted it into Excel format.
• 4) Created data visualizations for voting trends in various booths, including bar graphs, pie charts, box plots, etc.
• 5) Calculated the expected vote gain in the upcoming election.

Mar 2019 – Jul 2019 · 4 mos · Gurugram, Haryana, India

• 1) Managing the client database and analyzing the billing payment system (EPS) data.
• 2) Updating customer information using SQL queries and retrieving customer data as needed.
• 3) Converting and cleaning data from a NoSQL format to SQL, ensuring proper formatting and organization.
• 4) Performing data cleaning and structuring to ensure data was stored in an organized and accessible manner for efficient data retrieval.
• 5) Writing SQL queries and defining tables to facilitate various data storage requirements for dynamic web applications, ensuring the data was structured to support the website's needs.