Beacon Biosignals is seeking a talented engineer to help us ingest petabytes of EEG data and make it truly useful to the world.


  • You've encountered the myriad idiosyncrasies inherent to storing, streaming, and analyzing large volumes of dense signal data (e.g. audio, video, domain-specific sensor data, etc.).

  • 3NF is generally table stakes for any relational schema you design.

  • Migrations fill you with a sense of excitement rather than dread, because your data layer just leveled up. Besides, you automated away most minor migration-related pain points a long time ago anyway.

  • You don't have any particular need to work with a pure monolithic architecture or a pure microservices architecture. For you, characterizing service boundaries is an architectural design decision driven by resource profile, operational cost/benefit, and product need.

  • You have a tried-and-true workflow for debugging cross-service performance issues and selecting the layer of the stack that actually merits optimization.

  • You've witnessed some truly weird (un)structures in clinical data, but at the same time, you know from experience that designing The One True EMR is actually just falling down The One True Rabbit Hole.

  • You are as comfortable optimizing bare-metal custom GPU kernels as you are orchestrating robust networks of source-specific ingest pipelines.

  • You know from experience that a well-designed K8s cluster can provide an essential, unified ontology for resource/workflow orchestration, while a poorly designed K8s cluster can make developers reconsider getting into software development in the first place.

  • You're a reproducibility/containers nerd who turns data scientists into reproducibility/containers nerds.

  • You've tried just about every "git but for dense models/data" solution out there.

  • You prefer open-source dependencies to closed-source dependencies because you have a compulsion to read the code that you're running.

  • You think Hasura is cool.

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