Vinayak Joshi

Software Engineer

Pune, Maharashtra, India4 yrs 3 mos experience

Highly Stable

Key Highlights

Experienced in Machine Learning and Deep Learning applications.
Developed innovative voice-based solutions using NLP frameworks.
Strong background in statistical analysis and data processing.

Stackforce AI infers this person is a Machine Learning and Data Science professional with experience in SaaS and Healthcare.

Contact

hivinuravi.joshi2000@gmail.com LinkedIn

Skills

Core Skills

Machine LearningWeb DevelopmentDeep LearningData Science

Other Skills

Transfer LearningFlaskGoogle Speech Recognition APINLP frameworksStatistical AnalysisImage ProcessingStrategic PlanningData StructuresMicrosoft OfficeMicrosoft PowerPointMicrosoft ExcelMicrosoft WordPythonC++C (Programming Language)

About

I am a passionate software engineer working at Microsoft

Experience

4 yrs 3 mos

Total Experience

4 yrs 3 mos

Average Tenure

4 yrs 3 mos

Current Experience

Microsoft

3 roles

Software Engineer 2

Promoted

Feb 2025 – Present · 1 yr 3 mos

Software Engineer

Jul 2022 – Present · 3 yrs 10 mos

SWE Intern

Jan 2022 – Jun 2022 · 5 mos

Samsung india

Samsung Prism Developer

Oct 2020 – Feb 2021 · 4 mos · India

Fortune tech

Machine Learning Intern

Apr 2020 – Jun 2020 · 2 mos · Pune/Pimpri-Chinchwad Area

Worked on Transfer Learning applications and deployed them on to a Flask Web app. Implemented Google speech recognition API along with NLP frameworks to develop a voice-based form.

Transfer LearningFlaskGoogle Speech Recognition APINLP frameworksMachine LearningWeb Development

Nus computing

Deep learning intern

Dec 2019 – Jan 2020 · 1 mo · Singapore

○ Studied about different fitness activities collected 2500+ images to form a dataset.
○ Performed statistical analysis on the number of people concerned about fitness and are doing certain activities incorrectly.
○ Trained the model on 2500+ images belonging to 5 different classes. Tested the model through video processing.
○ The model would give the correct image of the activity if done inaccurately by the user.
○ Achieved an accuracy of 78%.

Statistical AnalysisImage ProcessingDeep LearningData Science

Hewlett packard enterprise

Data analytics and Deep learning intern

Dec 2019 – Dec 2019 · 0 mo · Singapore

Modeled a Fitness activity classication system that would predict the exercise done by a person through video processing and depict the correct picture of the activity if done wrong. Successfully got it approved by HPE and NUS trainers.