Senior Scientist, Synthetic Data Generation

What you'll do

• Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation.
• Produce datasets to improve pre- and post-training for models like Nemotron.
• Advance multimodal synthetic data generation for image, document, video, and audio.
• Design and maintain open-source libraries and SDKs with clean APIs and documentation.
• Drive software excellence using modern tooling, configuration-based architecture, and CI-CD.
• Publish original research at top machine learning and AI conferences.
• Mentor interns and junior researchers to develop technical growth within the team.

What we're looking for

• PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.
• 3+ years of research experience in synthetic data generation, generative modeling, multimodal machine learning, or related areas.
• Deep technical understanding of LLMs, data shaping for pre- and post-training, and inference frameworks like 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, or ACL.
• Open-source contributions in ML or data tooling (preferred).
• Experience with multimodal generation or understanding, such as vision-language, document AI, video, or audio (preferred).
• Experience building and optimizing scalable data pipelines for large-scale model training (preferred).