About Us
We're a stealth startup building the first health platform that implements true causal inference on multi-omic data, not another correlation dashboard. You'll architect a system that solves the fundamental challenge of harmonizing vastly different biological timescales - from millisecond HRV oscillations to 6-month methylation drift - while implementing counterfactual reasoning that can definitively answer, questions like: "What would your DunedinPACE aging score be without this intervention?" This means building production-grade Structural Causal Models with proper backdoor adjustment, implementing propensity score matching on observational health data, and creating a real-time inference engine that processes 100Hz physiological streams against epigenetic baselines. You've likely built and scaled data pipelines processing billions of events, deployed ML models that handle temporal confounding, and have opinions on when Pearl's do-calculus beats potential outcomes frameworks. Phase 1 alone requires seamlessly integrating methylation panels with wearable device’s autonomic measurements to quantify how today's 12% HRV improvement impacts next year's biological age - with causal certainty, not correlation.
Technical bar
You've architected systems at scale (not just contributed features), have published or could publish on your technical work, and can debate the merits of different causal discovery algorithms. We are looking for someone who's implemented LSTM networks for physiological time-series, knows why RMSSD matters more than SDNN for parasympathetic tone, and understands why methylation at the AHRR locus beats self-reported smoking data. Healthcare experience (FHIR/HL7) helps but isn't required if you've built complex systems elsewhere. This role should be able to operate with guidance from our CTO with deep-tech expertise, but you'll own entire architectural decisions from day one. Remote-first, meaningful equity reflecting founding team status. If you've been waiting to apply causal inference to genuinely extend human healthspan - and have the technical depth to build it properly - reach out with specific examples of systems you've architected and scaled.