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Zyphra

Open-source AI company building multimodal agents

Research Engineer - Brain Computer Interface Models

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Taking ownership of a project component, communicating the process clearly, and delivering a working module.
  • Excellent communication and collaboration skills, with clean and concise coding practices.
  • Strong implementation and prototyping skills across research and engineering at scale.
  • Ability to learn new domains quickly, orient oneself in academic literature, and implement new ideas by applying concepts from other modalities to electroencephalography.
  • Interest in neural data such as electroencephalography, magnetoencephalography, and functional magnetic resonance imaging, as well as building foundation models.
  • Proficiency with PyTorch and Python.

Responsibilities

  • Conduct large-scale electroencephalography model training runs and evaluation.
  • Perform architecture and training methodology ablations and innovations.
  • Collect and preprocess datasets for electroencephalography and other brain-computer interface modalities.
  • Optimize the performance of the training stack.
  • Integrate models into real-world brain-computer interface applications.

Desired Qualifications

  • Experience with variational autoencoders, generative adversarial networks, diffusion models, and contrastive learning.
  • Familiarity with signal processing, especially for electroencephalography, and time-series analysis.
  • Experience training on large-scale, multi-node graphics processing unit clusters.
  • Experience contributing to large existing codebases and ramping up quickly.
  • Previously published machine learning research in well-respected venues.

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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