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Research Intern AI

IBM

Updated on: 20 September 2024

Additional Details

Website

www.ibm.com

website

Work Location

Bengaluru, Gurgaon

location

Job Type

FTE

job_type

Batch

2025

batch

Stream Required

BE/B-Tech/ME/M-Tech

stream

Salary

5-7 LPA (Expected)

salary

Job Description

 

Introduction
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk

Your Role and Responsibilities

 

Summer Internship Program is one of the major activities under the University Relation Program. IBM Research India offers Summer Internship to the bright students of leading technical Universities in India. IBM Research India provides industry experience and world class technologies to these students to show their talent. During internship students work on current projects happening in the lab, they solve problems with the help of their mentors. Idea is to give industry experience to the students and look for future employees.

  • Growth Path
  • Can be converted to regular hire based on performance
  • Skills required
  • Excellent coding skills in Java/Python (including pandas, NumPy), Data Structures, Algorithms, Problem Solving, linear algebra, probability, statistics, Experience with VS Code, Jupyter notebooks,Git
  • AI/ML fundamentals (supervised and unsupervised learning, classification, regression, neural networks, clustering etc), Learning fundamentals, Data Manipulation and Analysis for large data, AI libraries/frameworks such as TensorFlow/PyTorch, Deep Larning, Foundation Models, Large Language Models, Experience of working with platforms such as Watsonx.ai or similar


Required Technical and Professional Expertise

  • Excellent coding skills in Java/Python, Data Structures, Algorithms, Problem Solving, AI/ML fundamentals (supervised and unsupervised learning, classification, regression, neural networks, clustering etc)


Preferred Technical and Professional Expertise

  • AI libraries/frameworks such as TensorFlow/PyTorch, Jupyter notebooks, Deep learning fundamentals, Data Manipulation and Analysis for large data, tools (pandas, NumPy), linear algebra, probability, statistics, Git, Containerization (Docker/Kubernetes/ Openshift)

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