Akhilesh Kapse

Senior Software Engineer

Nagpur, Maharashtra, India5 yrs 10 mos experience

Key Highlights

Expert in leveraging LLMs for AI enhancements.
Proven experience in computer vision and deep learning.
Strong background in data analysis and machine learning.

Stackforce AI infers this person is a Data Scientist with expertise in AI, machine learning, and computer vision in SaaS.

Contact

Skills

Core Skills

Image ProcessingGenerative Adversarial Networks (gans)Sql

Other Skills

Big DataBootstrapC (Programming Language)Cascading Style Sheets (CSS)Computer VisionData AnalysisData ScienceDeep LearningDocker ProductsFast-APIFlaskGitlabGoogle Cloud Platform (GCP)HTML5JavaScript

About

I am a Data Scientist, currently working at gainsight on GEN AI and data analysis projects I enjoy leveraging CVs, LLMs, and machine learning to solve problems. In the past, I have worked on computer vision projects involving deep learning research into fluid simulation images, retail image background removal product development, and satellite imagery. Currently, I am focused on leveraging LLMs to enhance Gainsight's features and developing new GEN AI capabilities.

Experience

5 yrs 10 mos

Total Experience

1 yr 8 mos

Average Tenure

1 yr

Current Experience

Jiosaavn

Senior Software Engineer - Search

Apr 2025 – Present · 1 yr · Navi Mumbai, Maharashtra, India · On-site

Gainsight

2 roles

Associate Data Science Engineer

Jul 2023 – Mar 2025 · 1 yr 8 mos · Hyderabad, Telangana, India

AI Cheat Sheet
Enrich with AI
Gainsight Copilot

Data Science Intern

Jan 2023 – Jul 2023 · 6 mos · Hyderabad, Telangana, India

Amazon

Amazon ML Summer School

Jun 2022 – Jul 2022 · 1 mo

Fynd (shopsense retail technologies ltd.)

Machine Learning Engineer

May 2022 – Aug 2022 · 3 mos · Mumbai, Maharashtra, India

Visit- https://www.erase.bg/
◦Team: Worked with Pixel-Bin core team for improving EraseBG product and integrating ML solution in production backend using Fast-API.
◦ Research and work: Implemented car masking and shadow generation via image processing, car bottom-plane approximation by key-point detection (HRNet model), and using Generative Models(GANs)
◦ Impact: The model is employed on official Pixel-Bin site for commercial serving. (Shadow generation with image processing (Version-1) and by pix2pix generative-model (Version-2))

Image ProcessingBig DataGitlabGenerative Adversarial Networks (GANs)Fast-APIPyTorch

Kawa space

Data Science

Sep 2021 – Jan 2022 · 4 mos · Mumbai, Maharashtra, India

o Worked on Building Change detection and RVGI-biased crop classification modeling with multi-spectral remotely sensed satellite imagery and QGIS data processing.
o Research on various L0 (raw sensed data) to L1 conversion techniques. RVI and RVGI data collection via SQL quarries on GCP Big-Query and KAWA API calls.

SQL

Google developer student club - iiitdm jabalpur

AI/ML Lead

Aug 2021 – Jul 2022 · 11 mos

New york university

Machine Learning Researcher

May 2021 – Jul 2021 · 2 mos · United States

Developing Deep learning methods that can incorporate physical laws in a systematic manner is a key element in advancing AI for physical sciences.
o Explored research papers for implementing machine learning models for fluid interaction and analysis in collaboration
with NYU Ph.D. student to make the model more precise in flow physics scenarios.
o Design and implemented deep learning models for complex fluid masking and velocity field predictions (Unet, SRInet, Turbulent Flow-Net, DenseEd Lstm, etc).
o Used PIV high-speed camera for capturing the flow. MATLAB for manual masking and post-processing the frames for ML model feeding. PIVLAB for velocity field analysis and ground truth for the model.
o The project was able to gain considerable time and computational benefits over current flow stimulations techniques.

Appcilious pvt. ltd

ML Application Developer Intern

Aug 2020 – Sep 2020 · 1 mo · Bengaluru, Karnataka, India

o Worked with Object Detection Models and Segmentation Auto-Encoders in both TensorFlow and Pytorch framework.
o Full Stack web development of an application (DL model support at backend).
o Deploying real time application on web-services (Docker images on AWS and Heroku hosting using python Flask API)
o Experimenting and learning about Audio data processing and modeling. Build Speaker Recognition system. Achieved accuracy of around 90% on the test data and 82% on real-case voice data.