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About the Role

Eon is building the infrastructure for large-scale connectomics data collection, reconstruction, and brain simulation. We are seeking a machine learning, software, or data engineer with strong experience in large-scale neuroscience data pipelines to help build and optimize Eon’s connectomics reconstruction pipeline.

Responsibilities

• Build, optimize, and maintain large-scale connectomics data pipelines for volumetric microscopy data.
• Develop and improve machine learning workflows for image segmentation, affinity prediction, watershed/post-processing, synapse detection, and neural reconstruction.
• Work with large-scale n-dimensional image data, including TB- to PB-scale datasets.
• Run controlled ML experiments to improve segmentation accuracy, throughput, and reliability.
• Create polished, compelling visualizations of connectomic data, neural activity, and reconstructed circuits.
• Contribute to embodied simulations of animal models using connectome-derived neural architectures.

Requirements

• Strong experience in large-scale neuroscience data pipelines.
• Experience with connectomics, volumetric imaging, segmentation workflows, manual or semi-automated proofreading pipelines, and large-scale n-dimensional image data.
• Comfortable moving between ML experimentation, production data infrastructure, scientific computing, and computational neuroscience.
• Experience with large data systems, ideally at TB scale or above.
• Experience with computer vision, biological image segmentation, or volumetric data analysis.
• Strong software engineering skills, including clean code, version control, testing, documentation, and reproducible workflows.
• Strong communication skills and ability to collaborate with neuroscientists, microscopists, ML engineers, and data infrastructure engineers.

Skills

• Neuroglancer, BigDataViewer, Fiji/ImageJ, CloudVolume, TensorStore, Zarr, N5, DVID, CAVE, or related tools.
• Affinity prediction, watershed segmentation, flood filling networks, U-Nets, transformers for vision, or other computer vision models for biological image data.
• Distributed data processing, cloud infrastructure, GPU inference, and high-throughput ML pipelines.
• Large-scale n-dimensional array processing in Python, C++, Java, or similar environments.
• Strong ability to create polished and engaging visualizations.
• GPU kernel development experience is a definite plus.

Salary/Compensations

• Competitive salaries, including equity, apply.

About the Company

• Eon is building the infrastructure for large-scale connectomics data collection, reconstruction, and brain simulation.
• Our mission is to enable the safe and scalable development of brain emulation technology, beginning with digital twins of model organisms.
• We are developing an end-to-end platform that spans tissue preparation, high-throughput microscopy, large-scale image processing, neural reconstruction, connectome-based modeling, and embodied simulation.
• We are looking for exceptional engineers and scientists who can help turn biological brain data into usable computational systems.