Abhishek Patel

Software Engineer

Bhopal, Madhya Pradesh, India5 yrs 9 mos experience
Most Likely To SwitchHighly Stable

Key Highlights

  • Expert in Machine Learning and Python development.
  • Proven track record in developing complex software solutions.
  • Strong background in deep learning and algorithm optimization.
Stackforce AI infers this person is a Software Engineer with expertise in Machine Learning and Software Development.

Contact

Skills

Other Skills

CC++Cascading Style Sheets (CSS)DesignJavaScriptMachine LearningPythonSQLServer SideTemplatingjinja

Experience

5 yrs 9 mos
Total Experience
2 yrs 10 mos
Average Tenure
5 yrs 4 mos
Current Experience

Amazon

3 roles

Software Development Engineer II

Mar 2025Present · 1 yr 3 mos

Software Development Engineer II

Promoted

Jul 2023Mar 2025 · 1 yr 8 mos

System Development Engineer

Jan 2021Jun 2023 · 2 yrs 5 mos

Quantiphi

2 roles

Software Engineer

Aug 2020Jan 2021 · 5 mos

  • • Responsible for developing QInnovationHub portal end to end

Software Engineer

Jan 2020Aug 2020 · 7 mos

  • Added full text search capability in internal search engine leveraging Elasticsearch - POC
  • Worked on creating end to end frontend of Onboarding portal of Quantiphi
  • UI and Bug fixes on Content factory portal

National university of singapore

Research Intern

Jun 2018Aug 2018 · 2 mos · Singapore

  • Guide : Dr Dipti Srinivasan and Dr Anupam Trivedi.
  • Worked at Energy management and Microgrid Lab in the field of Evolutionary Computing.
  • Worked on a new technique to improve the existing differential evolution algorithms for single
  • objective optimization.
  • Proposed technique improved convergence ability of jDE, JADE algorithms significantly.
  • Tech stack - Matlab, Origin 2018.

Indian institute of technology, indore

Research Intern

Dec 2017Jan 2018 · 1 mo · Indore Area, India

  • Guide: Dr. Bhargav Vaidya
  • Worked at Center of Astronomy in the field of Deep Learning.
  • Implemented a deep learning model for Morphological classification of radio images two astrophysical jets using Convolutional neural network and data augmentation.
  • Significantly decreased the time required by researchers to organize images into different groups manually.
  • Able to get 92.4% of accuracy.
  • Tech Stack: Python, Keras, Matplotlib, Astropy, Tensorflow, Scikit Learn

Education

International Institute of Information Technology, Bhubaneswar

Bachelor of Technology (B.Tech.) — Computer science

Jan 2016Jan 2020

Kendriya Vidyalaya

PCM and Computer science

Jan 2004Jan 2016

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