Large-Language-Model (LLM) Research Scientist

Jobverse.io; Chapel Hill (NC); On-site; USD 150,000 - 230,000; Full time

Job summary

TAIRC in Chapel Hill, NC, seeks an LLM Research Scientist to advance training techniques and architectures for large language models. The role emphasizes rigorous research, experimental design, and collaboration across disciplines to push state-of-the-art methods.

The successful candidate will publish findings, contribute to open-source projects, and develop algorithms and tools for model training and optimization in a collaborative research environment.

Responsibilities

• Lead rigorous AI research: Conduct experiments to test and improve LLM architectures, training methods, and evaluation frameworks
• Design experiments: Plan and execute systematic studies to measure model performance, alignment, and robustness
• Collaborate across disciplines: Work with linguists, cognitive scientists, engineers, and policy experts to ensure models are inclusive and ethical
• Publish and disseminate results: Produce research papers, present at conferences, and contribute to open-source projects
• Develop algorithms and tools: Create new training algorithms, data augmentation techniques, and model compression methods

Job description

TAIRC is seeking an LLM Research Scientist to develop novel training techniques and architectures for large language models. The role focuses on conducting rigorous research, designing experiments, collaborating across disciplines, publishing findings, and developing algorithms and tools for model training and optimization.

Responsibilities

• Lead rigorous AI research: Conduct experiments to test and improve LLM architectures, training methods, and evaluation frameworks
• Design experiments: Plan and execute systematic studies to measure model performance, alignment, and robustness
• Collaborate across disciplines: Work with linguists, cognitive scientists, engineers, and policy experts to ensure models are inclusive and ethical
• Publish and disseminate results: Produce research papers, present at conferences, and contribute to open-source projects
• Develop algorithms and tools: Create new training algorithms, data augmentation techniques, and model compression methods