Ashish Gautam

Ashish Gautam

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Software Development Engineer
Los Angeles, California, United States

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Jobs verified_user 0% verified
  • Mesh
    Software Development Engineer
    Mesh
    Jan 2026 - Current (9 months)
    Building a next-generation digital identity and trust platform for professionals and businesses. I work on designing, developing, and scaling cloud-native systems that power identity verification, compliance, and real-time decisioning for B2B and financial services use cases.

    In this role, I contribute across the stack, with a strong focus on backend and cloud infrastructure, owning features end-to-end from design and implementation to testing, deployment, and production support.

    Key responsibilities:
    • Designing and building scalable backend services and APIs using AWS serverless technologies
    • Owning features end-to-end, from technical scoping and system design to deployment and monitoring
    • Solving co
Education verified_user 0% verified
  • University of Southern California
    Master's degree, Computer Science
    University of Southern California
  • Guru Gobind Singh Indraprastha University
    Bachelor of Technology - BTech, Electrical and Electronics Engineering
    Guru Gobind Singh Indraprastha University
  • R
    Ryan International School, Delhi, India
    Ryan International School, Delhi, India
Projects (professional or personal) verified_user 0% verified
  • D
    Dynamic Product Search Android App Development Project
    Nov 2023 - Dec 2023 (2 months)
    Passionate about transforming ideas into tangible, innovative solutions, I embarked on a solo journey to create a Dynamic Product Search Android App. This project reflects my commitment to delivering high-quality software, showcasing expertise in Android app development, RESTful API integration, and user-centric design.

    Key Features & Achievements:
    Independent Development: Spearheaded the entire development lifecycle of a Dynamic Product Search Android App, from conceptualization to implementation.
    Intuitive User Interface: Designed an engaging and user-friendly interface, prioritizing ease of navigation and real-time search functionality for a seamless user experience.
    Seamless Backend Communication: Implemented r
  • R
    Responsive Web Page Recreation using HTML & CSS
    Aug 2023 - Sep 2023 (2 months)
    I recently completed an insightful assignment focusing on crafting web pages with HTML and CSS, where the objective was to meticulously replicate a given static web page, aligning precisely with provided screenshots and a detailed walkthrough video. The endeavor was immensely successful and honed my skills in front-end web development technologies.

    Key Responsibilities:
    Authored clean, structured, and robust HTML and CSS code to emulate the design of the given web page without the aid of web development tools, relying solely on a text editor.
    Utilized five provided images, ensuring accurate cropping and placement to match the original design.
    Adhered strictly to the design specifications, including font styles, col
  • S
    Server-side Scripting with Python Flask, JSON, and eBay API
    Aug 2023 - Sep 2023 (2 months)
    Executed a comprehensive server-side scripting project harnessing the capabilities of Python, Flask framework, and eBay API to create a dynamic, user-friendly web page allowing users to seamlessly search items available on eBay.com. This cloud-hosted solution offered real-time search functionalities, offering results in a concise tabular format.

    Key Features:
    User-Centric Search Interface: Developed an intuitive, responsive web interface enabling users to input queries and receive corresponding eBay item listings.
    Cloud Integration: Deployed the backend on prominent cloud platforms such as AWS, GCP, or Azure, leveraging Python and F
  • O
    Optimized Meeting Scheduler with Multi-Server Architecture
    Jan 2023 - Apr 2023 (4 months)
    Engineered an innovative Meeting Scheduler System designed to streamline and expedite the process of coordinating meeting schedules, enhancing overall productivity and user experience. The system optimizes meeting arrangements by autonomously identifying suitable time slots based on participants’ availability, thereby reducing time and effort traditionally spent on coordinating schedules manually.

    Key Components:

    Client Interface:
    Facilitates user interaction, allowing users to input participant names.
    Displays optimal time slots received from the main server, enabling users to finalize meeting schedules seamlessly.

    Main Server (ServerM):
    Orchestrates the process by interfacing with client and
  • O
    Optimal Sequence Alignment Solution
    Jan 2022 - Apr 2022 (4 months)
    Project Overview:
    I led a pivotal project to develop an optimized Dynamic Programming solution for the Sequence Alignment problem, aimed at aligning two sequences, 𝑋 and 𝑌, to find the most efficient alignment with minimal cost, considering specific parameters and constraints.

    Algorithm & Implementation:
    The algorithm involved processing sequences to find optimal matching pairs, calculating alignment costs based on mismatch costs α and gap penalty δ. The primary goal was to attain alignments with minimal cumulative costs. The input strings were dynamically generated, ensuring accuracy in the sequences created for subsequent alignment processes.

    Technologies & Optimization:
    I leveraged Python, Java to c
  • M
    Machine Learning: Image Classification with Neural Networks
    Nov 2021 - Dec 2021 (2 months)
    This hands-on machine learning assignment on Google Colab involved training a neural network for image classification and classifying new, unlabeled images. The assignment covered the entire machine learning workflow, from data preparation to model training and evaluation.

    Key Steps:
    1. Connect to Google Drive: Linked Colab to Google Drive for data access and management.

    2. Data Preparation: Organized a dataset containing various images for training and validation.

    3. Model Training: Used a Jupyter notebook to set up and train the neural network, employing GPU acceleration for faster training.

    Challenges:
    1. Classification of New Images: Evaluated the model's ability to classify new imag
  • D
    Dynamic Geospatial Data Handling & Visualization
    Aug 2021 - Dec 2021 (5 months)
    This project involved an intricate understanding and application of geospatial data manipulation, visualization, and querying, focusing on the hands-on utilization of real-world spatial data. The initial phase required the generation of latitude and longitude pairs for nine distinct locations, ensuring variety and relevance in the sampled data. The accuracy of data collection was verified through onsite selfie proofs.

    Using Google Earth and KML file formatting, these locations were visualized, providing a visual depiction of the spatial coordinates. The project included the installation and implementation of spatial databases like Oracle Spatial, Postgres+PostGIS, allowing a comprehensive exploration of spatial functions and quer
  • M
    Machine Learning Exploration
    Aug 2021 - Dec 2021 (5 months)
    Leveraged Google Colab to delve into Machine Learning, building and training a Neural Network to distinguish between images of cats and dogs. This project provided exposure to the foundational workflow that underlies more intricate models like self-driving cars.

    Process & Implementation:
    Established a functional environment in Google Colab, connecting it to Google Drive, ensuring seamless data interaction.
    Organized and managed extensive datasets comprising 2,800 images (1,000 each for training and 400 each for validation).
    Trained the model using GPU acceleration, achieving significant speedup and efficiency, ensuring accurate learning from the given dataset.
    Implemented a hands-on approach, tuning, and runni
  • G
    Geospatial Data Handling Project
    Aug 2021 - Sep 2021 (2 months)
    I completed a Geospatial Data Handling project, which provided practical experience in collecting, visualizing, and querying geospatial data, enhancing my skills for real-world applications.

    Key Components:
    Data Collection: Gathered latitude and longitude pairs for 15 locations virtually, categorizing them into libraries, cafes, and waterworks.

    KML File Generation: Created a KML file for data visualization, organizing locations into categories for clarity.

    Google Earth Visualization: Used Google Earth for a visual representation of the data.

    Spatial Database Setup: Installed Oracle 11g+Oracle Spatial or Postgres+PostGIS, gaining proficiency in spatial functions.

    Spatial Queries: Ex
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