NVIDIA→
Research Scientist, Fundamental LLM Research for… at NVIDIA · Santa…
Entry LevelOn-siteFull-timeSanta Clara, CA$168k–$264k/yr
Skills
natural language processingdeep learninglarge language modelsmultimodal modelsdiffusion modelsknowledge distillationdata synthesistest-time inference algorithmsfactuality enhancementreasoning enhancementlong-context modelingagentic capabilitiesai safety
Job Description
Summary: NVIDIA is seeking a Research Scientist in the fields of NLP and deep learning research to contribute to our LLM Research team. The role involves researching and proposing alternative model architectures and methods to enhance language and multimodal models, along with contributing to the academic community through publications.
Responsibilities:
- Research and propose alternative model architectures that enhance the performance and efficiency of language or multimodal models
- Investigate novel methods for knowledge distillation and data synthesis for language or multimodal models
- Explore novel methods for test-time inference algorithms
- Analyze multiple novel methods for enhancing factuality, reasoning, long-context, or agentic capabilities of language or multimodal models
- Research: Undertake research, design, and implementation of novel methods aimed at enhancing the capability of large and small language models
- Publication: Contribute to the academic community by publishing original research findings in reputable conferences and journals
- Collaboration: Collaborate closely with fellow team members, as well as interdisciplinary teams within the company, to foster a collaborative research environment
- Mentorship: Provide mentorship and guidance to interns and students within the research team
- Technology Transfer: Collaborate with product groups within the university to facilitate the transfer of research technology into practical applications
Required Qualifications:
- Completing or recently completed a PhD in CS or equivalent research experiences in research labs with strong publication records at top-tier conferences
- A strong foundation in the theory and practice of NLP and deep learning
- Proficiency in all aspects of large language models from training to alignment to inference to evaluation is expected
- Alternatively, proficiency in all aspects of large multimodal models or diffusion models is expected
- A track record of outstanding research achievements and contributions
- Excellent communication skills to effectively convey research findings and collaborate with peers
Required Skills: Natural Language Processing, Deep Learning, Large Language Models, Multimodal Models, Diffusion Models, Knowledge Distillation, Data Synthesis, Test-time Inference Algorithms, Factuality Enhancement, Reasoning Enhancement, Long-context Modeling, Agentic Capabilities, AI Safety
Benefits: Equity, Benefits
Benefits
Equity
Benefits