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Solving the brain emulation problem so that humans can flourish in a world with AI superintelligence.

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EON Systems is an innovative company based in San Francisco, dedicated to empowering humanity through the development of whole-brain emulation technology. Their mission centers around creating the world’s largest connectome and the highest-fidelity brain emulation, paving the way for digital human intelligence. EON Systems aims to navigate the fastest path to achieving human-scale intelligence, ensuring a flourishing future for humanity.

The team comprises an international group of experts in neurobiology, artificial intelligence, and cognitive science, with a commitment to groundbreaking research and development. Notable advisors, including prominent figures like George Church and Stephen Wolfram, provide strategic guidance to accelerate the company's mission.

EON Systems not only focuses on technological advancements but also offers career opportunities for individuals passionate about harnessing intelligence. By subscribing to their updates, interested parties can stay informed about new breakthroughs in emulation technology. Through their efforts, EON Systems is at the forefront of making digital human intelligence a reality, shaping the future of technology and society.

Eon Systems

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At Eon, we are at the forefront of large-scale neuroscientific data collection. Our mission is to enable the safe and scalable development of brain emulation technology to empower humanity over the next decade, beginning with the creation of a fully emulated digital twin of a mouse.

## Role

We're a San Francisco team collecting very large microscopy datasets and we need an expert to design and implement our end-to-end data pipeline, from high-rate ingest to multi-petabyte storage and downstream processing. You'll own the strategy (on-prem vs. S3 or hybrid), the bill of materials, and the deployment, and you'll be on the floor wiring, racking, tuning, and validating performance.

Our current instruments generate data at ~1+ GB/s sustained (higher during bursts) and the program will accumulate multiple petabyes total over time. You'll help us choose and implement the right architecture considering reliability and cost controls.

## Outcomes (what success looks like)

- **Within 2 weeks:** Implement an immediate data-handling strategy that reliably ingests our initial data streams.

- **Within 2 weeks:** Deliver a documented medium-term data architecture covering storage, networking, ingest, and durability.

- **Within 1 month:** Operationalize the medium-term pipeline in production (ingest → buffer → long-term store → compute access).

- **Ongoing:** Maintain **≥95% uptime** for the end-to-end data-handling pipeline after setup.

## **Responsibilities**

- **Architect ingest & storage:** Choose and implement an on-prem hardware and data pipeline design or a cloud/S3 alternative with explicit cost and performance tradeoffs at multi-petabyte scale.

- Set up a sustained-write ingest path ≥1 GB/s with adequate burst headroom (camera/frame-to-disk), including networking considerations, cooling, and throttling safeguards.

- Optimize footprint & cost: Incorporate on-the-fly compression/downsampling options and quantify CPU budget vs. write-speed tradeoffs; document when/where to compress to control $/PB.

- Integrate with acquisition workflows ensuring image data and metadata are compatible with downstream stitching/flat-field correction pipelines.

- Enable downstream compute: Expose the data to segmentation/analysis stacks (local GPU nodes or cloud).

## **Skills**

- 5+ years designing and deploying high-throughput storage or HPC pipelines (≥1 GB/s sustained ingest) in production.

- Deep hands-on with: NVMe RAID/striping, ZFS/MDRAID/erasure coding, PCIe topology, NUMA pinning, Linux performance tuning, and NIC offload features.

- Proven delivery of **multi-GB/s ingest** systems and **petabyte-scale** storage in production (life-sciences, vision, HPC, or media).

- Experience building **tiered storage** systems (NVMe → HDD/object) and validating real-world throughput under sustained load.

- Practical S3/object-storage know-how (AWS S3 and/or on-prem S3-compatible systems) with lifecycle, versioning, and cost controls.

- Data integrity & reliability: snapshots, scrubs, replication, erasure coding, and backup/DR for PB-scale systems.

- Networking: 25/40/100 GbE (SFP+/SFP28), RDMA/RoCE/iWARP familiarity; switch config and path tuning.

- Ability to spec and rack hardware: selecting chassis/backplanes, RAID/HBA cards, NICs, and cooling strategies to prevent NVMe throttling under sustained writes.

## Ideal skills:

- Experience with **microscopy or scientific imaging** ingest at frame-to-disk speeds, including Micro-Manager-based pipelines and raw-to-containerized format conversions.

- Experience with life science imaging data a plus.

## Engagement details

- Contract (1099 or corp-to-corp); contract-to-hire if there's a mutual fit.

- **On-site requirement:** You must be physically present in **San Francisco** during build-out and initial operations; local field work (e.g., UCSF) as needed.

- **Compensation:** Contract, $100-300/hour

- **Timeline:** Immediate start

Data/Full Stack Engineer, Data Storage & Ingestion Consultant @ Eon Systems

A family of free and open source software operating systems based on the Linux kernel

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Full Stack Engineer

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Design and implement end-to-end data pipeline for large-scale neuroscientific data collection, focusing on storage and ingestion strategies.

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