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Output Biosciences

AI-driven preventative therapeutics for chronic disease

Member of Technical Staff - Pretraining

AI ResearchConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Have a PhD in computer science, machine learning, physics, mathematics, or a related field with 2+ years of post-doctoral or industry research experience, or a Bachelor's or Master's degree with 5+ years of hands-on research and engineering experience in representation learning and model pretraining.
  • Have a strong publication record at top-tier venues such as NeurIPS, ICML, or ICLR, with contributions to pretraining methods, self-supervised learning, representation learning, or foundation models.
  • Have hands-on experience pretraining large models on diverse, heterogeneous data, including designing training objectives and scaling training infrastructure.
  • Be proficient in Python and PyTorch, and have experience training models on distributed multi-GPU infrastructure.
  • Have demonstrated ability to own the full research-to-training pipeline, including training and shipping models, not only designing methods.
  • Write production-quality code that is well-tested and maintainable, and be comfortable working in shared codebases with version control and code review.
  • Design evaluations carefully, track experiments systematically, and draw conclusions from data rather than intuition.

Responsibilities

  • Advance the core architecture and training of the foundation model, from research through trained model, including designing architectures, developing training objectives, running large-scale pretraining, and evaluating model learning.
  • Develop methods for the model to learn across multiple biological data modalities simultaneously, building unified representations of molecular biology.
  • Extend the model's reasoning capabilities across biological phenomena, improving what it can predict and understand about binding, molecular properties, and biological function.
  • Own pretraining end-to-end, including experiment design, distributed training on multi-GPU clusters, hyperparameter optimization, and iteration.
  • Design evaluation frameworks to assess whether the model has learned biological reasoning rather than statistical patterns in training data.

Desired Qualifications

  • Have a background in chemistry, biology, computational biology, biophysics, or a related natural science.
  • Have experience pretraining models on molecular or biological data.
  • Have experience with multimodal learning or learning from heterogeneous data sources.
  • Have contributed to open-source machine learning projects.

About the Company

Output Biosciences

AI-driven preventative therapeutics for chronic disease

Output Biosciences develops preventative therapeutics to extend human healthspan by combatting chronic diseases. It uses computational biology and AI to discover therapies that can prevent diseases faster, with safer profiles and easier manufacturing, enabling quicker development timelines. The company differentiates itself by integrating biotech expertise with AI to create therapies focused on prevention, and by forming partnerships with pharmaceutical companies, licensing its technologies, and pursuing direct therapy sales. Its goal is to bring preventive treatments to market within months, shifting drug development toward stopping chronic diseases before they start.

Company size
1-10
Company stage
Seed
Total funding
$130K
Headquarters
New York City, New York
Founded
2020

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