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, let's talk.
Are you a student passionate about advancing AI technology and exploring innovative applications in generative AI, deep learning, and large language models (LLMs)?
Join our team at IBM Research, where we tackle exciting challenges in AI to drive impactful solutions and develop cutting-edge models and algorithms that shape the future of technology.
As a student researcher, you will work with a dynamic team on cutting-edge AI challenges. Your focus will include advancing Multimodal Retrieval-Augmented Generation (RAG) to integrate diverse data modalities, leveraging large language models (LLMs) for document understanding, and transforming unstructured data into structured formats. Additionally, you will design and train custom AI models. This role offers hands-on experience across diverse AI domains and provides an excellent opportunity to explore and contribute to various facets of AI research and application development.
Key focus areas of the team:
• Multimodal retrieval and cross-modality alignment techniques.
• Document analysis using LLMs and multimodal AI approaches.
• Embedding strategies, multimodal fusion, and vision-language modeling.
• Training and optimizing AI models, including exploring efficient model distillation techniques.
• Converting unstructured data into structured representations.
By joining us, you’ll gain hands-on experience in AI research and development, deepen your expertise in advanced AI techniques, and contribute to both theoretical and practical advancements in the field.
- Current M.Sc. or Ph.D. student in a relevant field (e.g., Computer Science, Electrical Engineering) with at least 2-3 semesters left
- Basic knowledge or coursework in Deep Learning, Computer Vision, or Natural Language Processing (experience with PyTorch or TensorFlow is a plus)
- Strong coding skills in Python
- Enthusiasm for learning and discussing recent advancements in Deep Learning methods
- A collaborative team player with good communication skills
Please add your grade sheet to your application