Principal Scientist, Synthetic Data & Multimodal AI

NVIDIA

New York (NY)

On-site

USD 272,000 - 431,000

Full time

2 days ago
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Job summary

NVIDIA seeks 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 for text, code, structured, and multimodal data, feeding pre- and post-training of LLMs such as Nemotron.

You will blend hands-on software engineering with applied research, mentor engineers, and collaborate with model teams, external labs, and product

Qualifications

  • PhD or equivalent experience in a relevant field.
  • 15+ years of engineering and research experience in synthetic data generation, generative modeling, multimodal ML, or related areas.
  • Deep technical understanding of LLMs, data shaping pre-training/post-training/RL, and inference frameworks such as vLLM or TGI.
  • Proven track record of developing or maintaining software libraries used by a broad developer community.

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 synthetic trajectories and RL components.
  • Advance multimodal synthetic data generation across image, document, video, and audio modalities.
  • Advance privacy-preserving and safe synthesis using differential privacy and de-identification.
  • 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
Generative modeling
Multimodal ML
Data pipelines
Publications
Open-source libraries

Education

PhD in Computer Science / ML or related

Tools

vLLM
TGI
CI/CD tooling

Job description

NVIDIA seeks 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 for text, code, structured, and multimodal data, feeding pre- and post-training of LLMs such as Nemotron.

You will blend hands-on software engineering with applied research, mentor engineers, and collaborate with model teams, external labs, and product

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