Research Scientist

Introduction

Are you eager to transform groundbreaking research into real-world solutions? Do you have a passion for developing cutting-edge AI systems that drive meaningful impact? Would you enjoy publishing in top-tier AI conferences and contributing to open-source advancements?

If so, we invite you to apply for our Research Scientist position at IBM. We are seeking highly motivated candidates with expertise in multimodal Large Language Models (LLMs) and a passion for governance and thrustworthy AI in the scientific domain.

Your Role And Responsibilities

We provide a engaging and motivating research environment, where you will be responsible for coming up with new innovative ideas, developing solutions working as a team, building prototypes, publishing research papers and demonstrating the value of your ideas in an enterprise setting.

Some Of Our Current Areas Of Work

• Long-form Factuality in LLMs
• Agentic workflows
• Evaluaiton of veracity of scientific claims
• Guardrails deployed in multi-modal settings
  
  

The succesfull candidate will work in close collaboration with the biggest partners of IBM Research on groundbreaking research

Preferred Education

Doctorate Degree

Required Technical And Professional Expertise

• An honored degree in computer science, applied mathematics or similar
• Basics of Machine Learning and AI: knowledge of ML fundamentals and common Deep Learning architectures; experience with AI/ML libraries such as Pytorch.
• Good programming skills: Python, version control, ability to write complex code from scratch and extend existing codes.
• Strong interest in performing basic research work, including: evaluation of existing literature, ideation of possible/alternative solutions, writing research papers.
• Ability to move quickly from idea to software prototype for evaluation and demonstration.
• Excellent spoken and written English.
  
  

Preferred Technical And Professional Experience

• A background in computational and/or data-driven methods.
• Familiarity with NLP
• Knowledge of GenAI approaches: model architectures, fine-tuning, transfer learning.
• Advanced Programming skills: Python, data preprocessing (pandas, xarray), experience with HPC and Cloud environments.
• Track record of published academic papers.