Introduction
At IBM Research, we are the innovation engine of IBM. Exploring what's next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You'll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world.
Your Role And Responsibilities
IBM Research AI Foundations is looking for a talented and highly motivated researcher to help advance our effort on creating the most efficient foundation models, while publishing works in the most prestigious AI conferences in the world. The candidate will be responsible for conducting cutting-edge research on natural language processing, reinforcement learning, agentic model development, model architectural innovation, and developing prototype solutions to real-world problems, working closely with top-notch students and IBM scientists in a flexible and fun environment.
Preferred Education
Doctorate Degree
Required Technical And Professional Expertise
- Great problem solving skills, with a strong desire for quality and engineering excellence
- Ability to quickly prototype ideas and use creative approaches for solving complex problems
- Strong team player with excellent verbal and written communication skills
- Skills
- Strong programming skills (at least 2 years of experience)
- Experience with machine learning tools and frameworks such as TensorFlow, PyTorch etc. (at least 2 years of experience)
- Experience with large language models (at least 1 year of experience)
Preferred Technical And Professional Experience
- Publication in top AI conferences
- Experience with distributed training and inference of large language models
- Experience with LLM architectures, reinforcement learning, or agentic model development
