--- title: 'Data Infrastructure Engineer at Alljoined' canonical: 'https://feeny.ai/job/data-infrastructure-engineer-alljoined-san-francisco-hdnsfa556y1p' type: 'job' last_seen: '2026-09-07' --- # Data Infrastructure Engineer at Alljoined - **Company:** Alljoined - **Location:** San Francisco, CA - **Compensation:** $140k–$180k - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-03-14 - **Last confirmed live:** 2026-09-07 - **Apply:** https://jobs.ashbyhq.com/alljoined/3ba86bc8-dfa4-4b04-8d33-574a419103dc ## Job description ## ABOUT ALLJOINED Alljoined is creating a future where humans are fully understood and augmented by technology. Our work solves the communication bottleneck between humans and computers by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale EEG datasets to decode multimedia input, eventually moving to internal thought. We are state-of-the art in capabilities and are fully vertically integrated. Our goal is to develop a general consumer interface to completely transform how we can live our lives. We are actively growing our founding engineering team to build the underlying infrastructure that makes this ambitious future a reality. ## ABOUT THE ROLE As a Data Infrastructure Engineer, you will build the backend and hardware architecture that allows us to do high-quality and fast research. You'll be owning our entire data lifecycle, from building pipelines that process massive multimodal datasets (video, audio, text, time-series) to provisioning and managing both cloud and bare metal compute clusters we use to train on it. You will be powering our foundational model training by bridging the gap between physical neuro hardware and our central repositories, working alongside world-class researchers to ensure they have a high-throughput, low-latency pipeline straight to the GPUs. YOU MIGHT BE A GOOD FIT IF YOU - Have 3+ years of production software engineering experience with deep expertise in systems-level architecture and languages like Python, Rust, C++, or Go. - Have built and maintained high-performance ETL pipelines capable of processing, buffering, and storing terabytes of daily unstructured data. - Are comfortable architecting, provisioning, and maintaining bare-metal local compute clusters, storage servers, and high-speed networking for intensive ML workloads. - Have a background in handling continuous, highly concurrent data streams from heterogeneous hardware peripherals without data loss. - Are capable of working across hybrid environments to define storage topologies, manage databases (TimescaleDB, ClickHouse), and sync massive datasets between on-premise edge servers and the cloud (AWS/GCP/Azure). - Enjoy owning the entire technical lifecycle of infrastructure, from optimizing low-level I/O bound operations to production deployment. ## STRONG CANDIDATES MAY HAVE - A deep understanding of modern ML frameworks (PyTorch/TensorFlow) and know how to build datasets that maximize and saturate GPU utilization. - Experience managing networking for distributed GPU training (InfiniBand, RoCE) or optimizing zero-copy networking and shared memory. - Built infrastructure involving programmatic video processing (FFmpeg, GStreamer, OpenCV) ## COMPENSATION RANGE $140,000 - $180,000/year While this represents our expected range based on market data, final compensation will be determined based on your specific skills and experience and may be outside this range. ## BENEFITS - Competitive equity compensation at a seed stage startup - Options for housing support - Visa sponsorship - 3% 401k matching - Health insurance ## About Alljoined ## Company Overview - **One-liner**: Alljoined develops neural decoding technology to interpret thoughts from brain signals non-invasively, aiming to bridge human cognition and technology by applying deep learning to EEG and fMRI data. - **Entity Type**: Private (Seed round, January 2025) - **Headquarters**: San Francisco, California, United States - **Founded**: 2023 - **Founders**: Not publicly disclosed (CEO is Jonathan Xu) ## Core Business - **Primary industries**: Research Services, Artificial Intelligence, Brain-Computer Interfaces (BCI) - **Target customers**: B2B (research institutions, healthcare providers), B2C (future consumer BCI applications); currently research‑focused - **Mission statement**: “Create a future where people can better understand themselves and connect with technology” – developing neural decoding to augment human capability and dignity ## Products & Services - **ENIGMA Model**: A multi‑subject EEG‑to‑image decoding model that learns a shared visual language across brains, enabling adaptation to new users in minutes. Achieves state‑of‑the‑art accuracy (demonstrated in peer‑reviewed work). - **MindEye2**: Multi‑subject fMRI‑to‑image architecture that trains 40× faster than prior models while matching performance (ICML 2025). - **Public EEG Dataset**: Largest public dataset for EEG‑image decoding – 6+ hours of recordings per participant across 20 subjects using consumer‑grade hardware. - **Proprietary Research Models**: Decoding of semantic content, emotion, inner speech, and intentional planning from brain signals. All offerings are research‑stage technology, not yet commercialized (pre‑revenue). ## Market Standing - **Valuation / Total Funding**: Not disclosed (Seed round in Jan 2025, 2 investors) - **Key Metric**: Total funding amount not publicly available; headcount 12 employees (LinkedIn) with conflicting report of 9 (BuiltIn) - **Notable Investors & Advisors**: - Individual investors include **Jeff Dean** (Chief Scientist, Google), **Guillermo Rauch** (CEO, Vercel), **Anastasis Germanidis** (Co‑founder, RunwayML), **Oliver Cameron** (Co‑founder, Odyssey), **Vas Bailey**. - Scientific Advisory Board: **Dr. Anil Seth** (Professor, University of Sussex), **Dr. Rufin VanRullen** (CNRS), **Dr. Arnaud Delorme** (Chief Architect of EEGLAB), **Dr. Thomas Naselaris** (University of Minnesota), **Dr. Tanishq Mathew Abraham** (CEO, MedARC). - **Growth Signals**: - Headcount grew **+142.9% YoY** (LinkedIn); currently 7 open positions across research and engineering. - Published papers at **ICML 2025** (MindEye2) and **CVPR** (mental imagery reconstruction from fMRI, highlight paper). - Released the largest public EEG‑image decoding dataset and demonstrated log‑linear neural scaling laws. ## Competitive Advantages - **Non‑invasive decoding**: Uses consumer‑grade EEG, making BCI practical for widespread use. - **Multi‑subject learning**: Models (ENIGMA, MindEye2) generalize across individuals, reducing calibration time from hours to minutes. - **Cutting‑edge research**: Peer‑reviewed publications at top ML/vision conferences; team includes world‑class neuroscientists and ML researchers. - **Ethical positioning**: Focus on augmenting human capability and dignity, not replacement. ## Strategic Focus - Decoding increasingly complex cognitive processes (emotion, inner speech, planning, abstract reasoning). - Scaling neural decoding through larger datasets and more powerful models. - Building a practical, non‑invasive interface for mental health, self‑understanding, and human‑computer interaction. ## Why Work Here - **In‑office culture** in San Francisco, CA (all roles require on‑site presence). - **Early‑stage environment** with ability to shape foundational technology; currently 12 employees. - **Research‑heavy team** – roles include Machine Learning Researcher, Computational Neuroscientist, Data Infrastructure Engineer, Software Engineer. - **Mission‑driven** – “improving human capability and dignity” with a focus on ethical augmentative AI. - **World‑class advisors** from top institutions (Google, CNRS, Princeton, etc.) and a highly collaborative team (former employees from Tesla, Snowflake, Microsoft, etc.). ## Sources 1. [alljoined.com](https://www.alljoined.com/) 2. [alljoined.com/about](https://www.alljoined.com/about) 3. [linkedin.com/company/alljoined](https://www.linkedin.com/company/alljoined) 4. [builtin.com/company/alljoined-inc](https://builtin.com/company/alljoined-inc) 5. 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