Principal Research Scientist, Synthetic Data Generation

• Build and scale data generation pipelines using LLM-based methods combined with automated quality evaluation. resulting in datasets to improve both initial training and fine-tuning of LLMs such as Nemotron. These data pipelines cover reasoning, coding, structured output, and multimodal understanding.
• Pioneer data generation for agentic and tool-use training: synthetic trajectories, multi-turn interactions, function calling, and executable environments for reinforcement learning, including reward modeling and verifiable-reward data
• Advance multimodal synthetic data generation - image, document, video, and audio - in partnership with NVIDIA’s model teams.
• Advance privacy-preserving and safe synthesis - differential privacy, anonymization, and de-identification - enabling model training on sensitive data in regulated domains.
• Develop and maintain open-source libraries and SDKs with clean APIs and strong documentation.
• Drive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD.
• Publish original research at top machine learning and AI conferences to maintain NVIDIA’s technical leadership.
• Mentor scientists and engineers across the team, raising the technical bar and growing the next generation of researchers.

• PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.
• 15+ years of engineering and research experience in synthetic data generation, generative modeling, multimodal machine learning, or related areas.
• Deep technical understanding of LLMs, how data shapes their pre-training, post-training, and RL stages, and inference frameworks such as vLLM or TGI.
• Proven track record of developing or maintaining software libraries used by a broad developer community.
• Experience building and optimizing scalable data pipelines for large-scale model training - throughput, distributed inference, and cost at cluster scale.
• Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar.

Ways to stand out from the crowd:

• Significant open-source contributions in ML or data tooling, with community adoption.
• Experience with multimodal generation or understanding (vision-language, document AI, video, or audio).
• Experience generating data for agentic, tool-use, or reinforcement-learning post-training, including RL environment design.
• Background in differential privacy, de-identification, or synthetic data for regulated industries such as healthcare, finance, or government.
• Experience influencing model training decisions at frontier scale, or partnering directly with pre-training and post-training teams.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, we want to hear from you.