Principal Scientist: Open-Source Synthetic Data for LLMs

NVIDIA; Colorado; On-site; USD 272,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Principal Scientist to set the technical direction for synthetic data generation across its frontier model efforts. You will define and build open-source libraries within the NVIDIA NeMo ecosystem that generate synthetic datasets feeding pre-training and fine-tuning of LLMs such as Nemotron.

This role combines hands-on software engineering with applied research in generative methods, and you will collaborate with research, engineering, product, and model teams as well as

Qualifications

• PhD or equivalent experience in Computer Science, ML, Statistics or related field.
• 15+ years of engineering and research experience in synthetic data generation, generative modeling, or multimodal ML.
• Deep technical understanding of LLMs and data influence on pre-training, post-training, and RL stages.

Responsibilities

• Build and scale data generation pipelines using LLM-based methods with automated quality evaluation.
• Pioneer data generation for agentic and tool-use training, including reinforcement learning data.
• Advance multimodal synthetic data generation (image, document, video, audio) in partnership with model teams.
• Develop and maintain open-source libraries and SDKs with clean APIs and documentation.
• Publish original research at top ML/AI conferences and mentor team members.

Skills

LLMs & data shaping

Software libraries development

Data pipelines for large-scale models

Academic publishing

Education

PhD in Computer Science or related field

Tools

vLLM

TGI

Job description

NVIDIA is seeking a Principal Scientist to set the technical direction for synthetic data generation across its frontier model efforts. You will define and build open-source libraries within the NVIDIA NeMo ecosystem that generate synthetic datasets feeding pre-training and fine-tuning of LLMs such as Nemotron.

This role combines hands-on software engineering with applied research in generative methods, and you will collaborate with research, engineering, product, and model teams as well as