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Research Scientist, Post-Training

DatologyAI· Research
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Hybrid (San Mateo HQ)$180k - $300kFull-timePosted 11mo ago

About the role

Research Scientist to lead post-training data curation for foundation models, bridging pre-training and post-training data curation, and turning research ideas into real-world impact.

Responsibilities

  • Post-training data curation. You’ll conduct research on how to algorithmically curate post-training data—e.g., how to generate and refine preference and instruction-following data, how to curate capability- and domain-specific data, and make post-training more effective, controllable, and generalizable.
  • Unifying pre-training and post-training data curation. Pushing the bounds on model capabilities requires unifying post-training and pre-training data curation. You will pursue research on end-to-end data curation: how to curate pre-training data to improve the post-trainability of models and how to jointly optimize pre- and post-training data curation, all in service of maximizing the final performance of post-trained models.
  • Transform messy literature into practical improvements. The research literature is vast, rife with ambiguity, and constantly evolving. You will use your skills as a scientist to source, vet, implement, and improve promising ideas from the literature and of your own creation.
  • Conduct science driven by real-world needs. Your research will be guided by concrete customer needs and product improvements.

Qualifications

  • 3+ years of deep learning research experience
  • Experience with post-training large vision, language, and multimodal models
  • Post-training algorithm development, data curation, and/or synthetic data methods for:
  • - Preference-based tuning (e.g. DPO, RLVR, RRHF)
  • - Alternative supervision & self-supervision techniques such as self-training and chain-of-thought distillation
  • - SFT (e.g. instruction tuning and demonstration fine-tuning)
  • Post-training tooling development and engineering experience
  • Strong understanding of the fundamentals of deep learning
  • Sufficient software engineering + deep learning framework (PyTorch or a willingness to learn PyTorch) skills to conduct large-scale research experiments and build production prototypes.
  • Demonstrated track record of success in deep learning research, whether papers, tools, or other research artifacts.

Skills

Required:Post-training data curationUnifying pre-training and post-training data curationLiterature to practical improvementsScience driven by real-world needs

Benefits

  • 100% covered health benefits (medical, vision, and dental).
  • 401(k) plan with a generous 4% company match.
  • Unlimited PTO policy
  • Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Daily lunches and snacks are provided in our office!
  • Relocation assistance for employees moving to the Bay Area.
Last updated Oct 22, 2026. Interested? Apply on the company site.
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Train Better Models, Faster and Smaller

DatologyAI automatically curates model training data. Train faster, achieve better performance, and reduce costs with enterprise-grade data curation.

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