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IBM

Data Scientist-Artificial Intelligence

IBM

Published 08 May 2026
Bangalore, India
Full Time

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Role Highlights

Languages used

Python
JavaScript

Key skills

AI
Data Analysis
NLP
Machine Learning
Integrations
Operating Systems
Image processing
foundation model
LLMs
Cloud
Research
ProtoTyping
Deployment
NOSQL
Optimization
UI
Bootstrap

Tools, Libraries and Frameworks

HuggingFace
IOS
Red Hat
IBM
GitHub
Kubernetes
AWS
Azure
GCP
PostGres
MongoDB
Ember
Linux
IOS SDK
Android
Tensorflow
PyTorch
Keras
React
JQuery

Description

The role involves architecting and delivering artificial intelligence solutions to address complex business challenges. Professionals will manage the entire project lifecycle, ranging from initial research and prototyping to final production deployment. The work requires processing and analyzing both structured and unstructured data to create cognitive solutions. Collaboration with various stakeholders is essential to leverage artificial intelligence for driving business value. Additionally, the position focuses on optimizing solutions through specialized processing techniques.

Required Qualifications and Skills

The role requires proficiency in Python and AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face. Candidates must possess a deep understanding of machine learning and natural language processing methods, along with experience in managing the full AI project lifecycle. Technical expertise in cloud platforms like AWS, Azure, GCP, and Kubernetes is necessary, as is experience with various database systems. Familiarity with tools such as Github Copilot and Amazon Code Whisperer is also required.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

IBM

Size

305978

Website

ibm.com

HQ

Armonk, New York, US

Public/Private

Public Company

Description

IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.

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