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Sushrut A. - Fullstack Developer, Django, Docker

Working at Softaims has been an experience that continues to shape my perspective on what it means to build quality software. I’ve learned that technology alone doesn’t solve problems—understanding people, processes, and context is what truly drives innovation. Every project begins with a question: what value are we creating, and how can we make it lasting? This mindset has helped me develop systems that are both adaptable and reliable, designed to evolve as business needs change. I take a thoughtful approach to problem-solving. Instead of rushing toward quick fixes, I prioritize clarity, sustainability, and collaboration. Every decision in development carries long-term implications, and I strive to make those decisions with care and intention. This philosophy allows me to contribute to projects that are not only functional, but also aligned with the values and goals of the people who use them. Softaims has also given me the opportunity to work with diverse teams and clients, exposing me to different perspectives and problem domains. I’ve come to appreciate the balance between technical excellence and human-centered design. What drives me most is seeing our solutions empower businesses and individuals to operate more efficiently, make better decisions, and achieve meaningful outcomes. Every challenge here is a chance to learn something new—about technology, teamwork, or the way people interact with digital systems. As I continue to grow with Softaims, my focus remains on delivering solutions that are innovative, responsible, and enduring.

Main technologies

  • Fullstack Developer

    5 years

  • Computer Vision

    2 Years

  • Python

    4 Years

  • TensorFlow

    2 Years

Additional skills

  • Computer Vision
  • Python
  • TensorFlow
  • Flask
  • DevOps
  • GitHub
  • RESTful API
  • Google Cloud
  • Django
  • Docker

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Experience Highlights

Damage Detection

This was a Minimum Viable Product built using Instance Segmentation. Frontend was built on React Web framework. Backend developed using FastAPI and database on PostgreSQL. We used Tensorflow Keras for deep learning and used Mask RCNN for Instance Segmentation to mask the vehicle damage output. Before passing the image to the main module our damage detector engine would do some quality control to ensure that the vehicle image is authentic and used some additional Third Party APIs to fetch the vehicle details from their database which would be helpful in estimating the damage claim cost.

A machine vision product

This is a handheld device which takes feed from webcam deployed inside a robust machine as you can see in the picture, clips taken are then being passed on to a remote device Jetson Nano. This device is much more robust than rasbperry pi and uses gpu. The device is configured with deep learning libraries. For this project I have used Tensorflow, OpenCV and Tiny Yolo v2. Model was converted into tflite to reduce latency.

Pytorch Project

Execute a Github code based on pytorch and nlp event prediction.

nsvision

nsvision is a python library that contains a set of tools required for image processing and data augmentation. It provides utilities for structuring image data.

Education

  • Anglia Ruskin University

    Master of Science (MS) in Computer science

    2023-01-01-2025-01-01

  • St. Vincent Pallotti College of Engineering and Technology

    Bachelor of Engineering (BEng) in Information Technology

    2015-01-01-2018-01-01

Languages

  • English
  • Hindi
  • Marathi (Marāṭhī)

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