Note: The job is a remote job and is open to candidates in USA. NVIDIA is at the forefront of the AI revolution, and they are seeking a Senior Scientist to advance their capabilities in synthetic data generation for training frontier models. The role involves building synthetic data generation pipelines, designing open-source libraries, and publishing research while collaborating with various teams.
Responsibilities
- Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron — reasoning, coding, structured output, and multimodal understanding
- Advance multimodal synthetic data generation — image, document, video, and audio — in partnership with NVIDIA's model teams
- Design 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 interns and junior researchers to develop technical growth within the team
Skills
- PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience
- A research background of 3+ years in synthetic data generation, generative modeling, multimodal machine learning, or related areas. Comparable experience is also considered
- Deep technical understanding of LLMs, how data shapes their pre- and post-training, and inference frameworks such as vLLM or TGI
- Proven track record of developing or maintaining software libraries used by a broad developer community
- Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar
- Open-source contributions in ML or data tooling
- Experience with multimodal generation or understanding (vision-language, document AI, video, or audio)
- Building and optimizing scalable data pipelines for large-scale model training (throughput, distributed inference)
- Experience generating data for agentic, tool-use, or reinforcement-learning post-training
Benefits
- You will also be eligible for equity and [benefits](https://www.nvidia.com/en-us/benefits/).
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