Abhishek Mathur

Software Engineer

Bengaluru, Karnataka, India5 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Experienced in microservice architecture and containerized frameworks.
Hands-on experience with deep learning, CNNs, and NLP.
Active participant in competitive programming contests.

Stackforce AI infers this person is a Software Engineer with expertise in cloud technologies and machine learning.

Contact

Skills

Core Skills

Microservice Architecture

Other Skills

BashCC++Cascading Style Sheets (CSS)Competitive ProgrammingGame DevelopmentGitHTMLJavaScriptLinuxMachine LearningMySQLProgrammingPythonReact.js

About

I am currently a part of Regulated Cloud team in Google, India. I have experience working with containerised frameworks, microservice based architecture and similar. I like to explore new fields in technology which includes deep learning and neural networks. I have hands on experience working with CNNs and NLP. I am passionate about Algorithmic Problem Solving and actively participate in online programming contests on various platforms like Codeforces (matcoder) and Codechef.

Experience

Google

2 roles

Software Engineer III

Nov 2023 – Present · 2 yrs 4 mos

Software Engineer II

Jul 2021 – Oct 2023 · 2 yrs 3 mos

Spotnana

Software Engineer

May 2020 – Aug 2020 · 3 mos

Part of the very first batch of interns at the company
Worked with spring framework on microservice based architecture to integrate end-2-end flow of third party API services.

Spring FrameworkMicroservice Architecture

Iiit hyderabad

2 roles

Teaching Assistant

Promoted

Jan 2020 – May 2021 · 1 yr 4 mos

Courses: Software Engineering (Spring 2021), Software Systems Development (Monsoon 2020), Introduction to Software Systems (Spring 2020)
Target audience: Undergraduate + Postgraduate students

Member of Student Parliament

Mar 2019 – Apr 2021 · 2 yrs 1 mo

Software engineering research center, iiit hyderabad

Researcher

May 2019 – Jul 2019 · 2 mos · Greater Hyderabad Area

Worked on credibility assessment and ranking of the web results based on genre credibility and relevance order. Used specific ontologies for calculating relevance score based on webpage content.