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Zyphra

Open-source AI company building multimodal agents

Data Engineer - Multimodal Systems

Data EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • Strong implementation and prototyping ability.
  • The ability to take an idea from conception to experimentation quickly.
  • The ability to work effectively with others in a high-paced research setting.
  • The ability to rapidly learn new fields and implement new ideas.
  • The ability to communicate and collaborate effectively while working on research and engineering implementation at scale.
  • Experience collecting, handling, and processing large datasets.
  • Experience with parallel Python programming frameworks such as Dask.
  • Understanding of state-of-the-art dataset curation across modalities.
  • A meticulous approach to inspecting data and performing sanity checks.
  • A strong grasp of experimental methodology for rigorous ablations and other hypothesis testing.
  • Understanding of and interest in large-scale, highly parallel data processing pipelines.
  • Proficiency with PyTorch and Python.
  • Experience contributing to large pre-existing codebases and rapidly getting up to speed.
  • Previously published machine learning research in well-respected venues.

Responsibilities

  • Collect large-scale datasets across text, audio, and image modalities.
  • Design and work with highly efficient, parallelized data processing pipelines across modalities.
  • Design and run rigorous experimental ablations to demonstrate the impact of new data improvements.
  • Create, collect, and improve datasets and data pipelines across a variety of modalities.
  • Contribute across teams to support data and pipeline initiatives.

Desired Qualifications

  • A postgraduate degree in a scientific subject, such as Computer Science, Electrical Engineering, Mathematics, Physics, or Machine Learning.

About the Company

Zyphra

Open-source AI company building multimodal agents

Zyphra Technologies builds open-source, open-science AI focused on multimodal models and efficient inference across devices. It develops autonomous agent platforms for enterprises, with Maia as a multimodal general agent prototype that combines neural architectures, long-term memory, reinforcement learning, and continual learning for text and audio. The company also releases open projects like Zamba (a cost-efficient foundation model), Zamba2-2.7B (a fast, small language model), and Zyda (a 1.3 trillion token training dataset) to support research and development. Their goal is to enable personalized AI that runs offline across diverse hardware while sharing transparent research resources and strengthening AI silicon performance.

Company size
51-200
Company stage
Series B
Total funding
$621.4M
Headquarters
San Francisco, CA
Founded
2019

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