Senior Scientist, Synthetic Data Generation

What you'll do

• Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation.
• Develop datasets to improve reasoning, coding, structured output, and multimodal understanding for frontier models.
• Advance multimodal synthetic data generation across image, document, video, and audio formats.
• Design and maintain open-source libraries and SDKs with clean APIs and documentation.
• Drive software excellence using modern tooling, configuration-based architecture, and professional CI/CD pipelines.
• Publish original research at top machine learning and AI conferences to maintain technical leadership.
• Mentor interns and junior researchers to foster technical growth within the team.

What we're looking for

• PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.
• At least 3 years of research experience in synthetic data generation, generative modeling, or multimodal machine learning.
• Deep technical understanding of LLMs, training methodologies, and inference frameworks like vLLM or TGI.
• Proven track record of developing or maintaining software libraries for a broad developer community.
• Strong publication record at premier venues such as NeurIPS, ICML, ICLR, or ACL.
• Experience building and optimizing scalable data pipelines for large-scale model training.
• Experience with multimodal generation or understanding including vision-language, document AI, video, or audio.
• Experience generating data for agentic, tool-use, or reinforcement-learning post-training.