Rahul Kumar

Software Engineer

Bengaluru, Karnataka, India9 yrs experience

Most Likely To Switch

Key Highlights

Expert in full-stack web development with MEAN Stack.
Proficient in machine learning and data visualization.
Strong background in competitive programming.

Stackforce AI infers this person is a Full-Stack Developer with expertise in Web Development and Machine Learning.

Contact

Skills

Core Skills

Web DevelopmentMachine Learning

Other Skills

D3.jsMEAN StackReinforcement LearningC++CJavaScriptNode.jsMongoDBExpress.jsHadoopHTMLPythonJavaSQLProgramming

About

I have done my Integrated Post Graduation (B.Tech + M.Tech) from ABV-IIITM Gwalior(Indian Institute of Information Technology and Management,Gwalior). MY CGPA- 7.94 Profiles on various competitive programming sites: Codeforces : http://www.codeforces.com/profile/rahul73 Hackerrank : hhttps://www.hackerrank.com/ipg73 Hackerearth : https://www.hackerearth.com/@rahul62 Codechef : https://www.codechef.com/users/rahul73

Experience

9 yrs

Total Experience

1 yr 6 mos

Average Tenure

1 yr 7 mos

Current Experience

Oracle

Senior Member of Technical Staff

Oct 2024 – Present · 1 yr 7 mos · Bengaluru, Karnataka, India

Salesforce

Member Of Technical Staff

Apr 2022 – Aug 2024 · 2 yrs 4 mos · Bengaluru, Karnataka, India

Nutanix

Member Of Technical Staff - 3

Feb 2021 – Apr 2022 · 1 yr 2 mos · Bengaluru, Karnataka, India

Flipkart

Software Engineer

Mar 2018 – Feb 2021 · 2 yrs 11 mos · Bengaluru Area, India

Signzy

Software Developer

Jun 2017 – Mar 2018 · 9 mos · Bengaluru Area, India

Optmyzr

Software Developer Internship

May 2017 – May 2017 · 0 mo · Hyderabad Area, India

Cogneau systems private limited

Web Developer Intern

May 2016 – Jul 2016 · 2 mos · Gurgaon

Worked on data visualization using d3.js along with FrontEnd and BackEnd of the company site using MEAN Stack.

Abv-indian institute of information technology and management

Bachelor Thesis

May 2015 – Aug 2015 · 3 mos · Gwalior Area, India

Autonomous game playing agent using reinforcement learning. Modified traditional approach of single agent to multi-agent for increasing the efficiency and decreasing the training time.