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
This is for a 2025 summer internship with the following start dates: May - August or June - September for quarter system schools.
As an AI Platform Software Development Engineer Intern at IBM Research, you will play a pivotal role in driving the development, testing, and implementation of cutting-edge AI technologies. Your responsibilities will span various aspects of software development, including design, integration, and evaluation of AI models and algorithms, while collaborating with cross-functional teams to integrate AI solutions into real-world products and systems. In this role, you will have the opportunity to work on exciting research initiatives, assess the potential applications of emerging AI technologies, and showcase the value of these technologies to both IBM's businesses and strategic partners. You will be part of team of developers, designers, and researchers working together to push the boundaries of AI innovation.
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Required Technical and Professional Expertise
Candidate should be pursuing a Bachelor's Degree.
- Student enrolled in a Bachelor's level degree program in Computer Science or related fields
- Strong programming skills in languages such as Python, Java, or C/C++.
- Familiarity with AI/ML fundamentals, Large Language Models (LLMs), Generative AI concepts and techniques
- Familiarity with Cloud computing concepts, methodologies, and tools
- Curiosity for exploring new technologies and contributing to open-source projects
Preferred Technical and Professional Expertise
- Student Enrolled in Masters. * Coursework in machine learning algorithms, data structures, linear algebra, Natural Language Processing (NLP)
- Experience with machine learning frameworks, such as PyTorch, Hugging Face, TensorFlow
- Experience with container technologies (Docker, Kubernetes, Red Hat OpenShift)