IBM Research AI Internship aims to solve complex problems and unlock new opportunities by pioneering advancements in artificial intelligence, specifically focusing on the future foundations of AI and creating technologies the world relies upon to solve big challenges.
Requirements
- Foundational ML Knowledge: Familiarity with core concepts of modern AI, including Transformer architectures and Large Language Models (LLMs).
- Programming Proficiency: Experience with Python for software development, scripting, or prototyping.
- Technical Proficiency: Expertise in ML frameworks (PyTorch) and full-cycle development of algorithms and systems.
- Specialized Skills: Hands-on experience with generative AI (LLMs) and multimodal models.
Responsibilities
- Contribute to shaping the future foundations of artificial intelligence.
- Conducting end-to-end research that delivers real-world AI impact through a rigorous, responsible, and open innovation framework.
- Explore cutting-edge research areas, including new algorithms for training, fine-tuning, and inference time scaling, alongside pioneering work in generative computing and generative programming for language, code, and other modalities.
- Engage in the full research lifecycle to pioneer new advancements in artificial intelligence.
- Identify core challenges, designing novel prototype solutions, and validating them through rigorous experimentation.
- Develop the robust, scalable infrastructure that powers cutting-edge AI research.
- Transforming novel algorithms into high-performance, reusable code within modern, distributed frameworks, while contributing to IBM's open innovation initiatives.
Other
- High School Diploma/GED
- Problem-Solving: Strong analytical and quantitative skills with an ability to break down complex problems.
- Communication: Ability to clearly explain technical concepts and work collaboratively within a team.
- Learning Mindset: A strong interest in AI research and a commitment to building high-quality, well-tested code.
- Communication: Ability to present complex research and build high-impact technical demonstrations.
