Machine Learning Engineer, Connectomics

Eon Systems
San Francisco
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningSkills: ["Communication","Collaboration","Problem-solving","Software engineering"]

Build and optimize a connectomics reconstruction pipeline that turns raw microscopy into segmented neurons, synapses, connectivity maps, visualizations, and brain simulations. Work hands-on across ML experimentation and production-grade neuroscience data infrastructure, including segmentation, affinity prediction, watershed/post-processing, and neural reconstruction. Collaborate with cross-functional teams to improve accuracy, throughput, and reliability while scaling processing to TB–PB volumetric datasets and delivering polished visualizations.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Eon Systems
Eon Systems
1 month ago

Machine Learning Engineer, Connectomics

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and optimize a connectomics reconstruction pipeline that turns raw microscopy into segmented neurons, synapses, connectivity maps, visualizations, and brain simulations. Work hands-on across ML experimentation and production-grade neuroscience data infrastructure, including segmentation, affinity prediction, watershed/post-processing, and neural reconstruction. Collaborate with cross-functional teams to improve accuracy, throughput, and reliability while scaling processing to TB–PB volumetric datasets and delivering polished visualizations.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Build, optimize, and maintain large-scale connectomics data pipelines for volumetric microscopy data.
  • •Develop and improve ML workflows for image segmentation, affinity prediction, watershed/post-processing, synapse detection, and neural reconstruction.
  • •Process 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.

Key Requirements

  • •Strong experience building large-scale neuroscience data pipelines for volumetric microscopy data.
  • •Experience with connectomics workflows including segmentation, manual or semi-automated proofreading pipelines, and neural reconstruction.
  • •Hands-on machine learning workflow experience for image segmentation and affinity prediction, including watershed/post-processing and synapse detection.
  • •Ability to work with large-scale n-dimensional image data, including TB- to PB-scale datasets.
  • •Strong software engineering practices (clean code, version control, testing, documentation, reproducible workflows).
Experience:NeuroscienceConnectomicsComputer visionVolumetric imagingHigh-throughput data pipelines
Skills:CommunicationCollaborationProblem-solvingSoftware engineering
Tech Stack:NeuroglancerBigDataViewerFijiImageJCloudVolumeTensorStoreZarrN5DVIDCAVEPythonC++JavaGPU inference

Company Brief

Eon Systems
Developing high-fidelity brain emulation by building large-scale connectomes and using neurobiological data plus AI to create digital emulations (initial targets include Drosophila and mouse models).
Industry: Scientific Research
Company Size: Micro (1 to 10 employees)
Growth: Early Stage Startup
Headquarters: San Francisco, United States
WebsiteLinkedIn