About ElectroKare ElectroKare turns a signal almost everyone already wears — the EKG from a smartwatch or chest strap — into a non-invasive window on blood chemistry. Today that means real-time electrolyte and recovery insight for athletes.

The longer arc is bigger:

the same waveform that flags a potassium shift mid-workout can surface the earliest signatures of chronic kidney disease, long before conventional screening catches it. We're starting with performance and building toward detection that could change how kidney disease is caught at population scale. About the Role We're hiring a Chief Science Officer to own the scientific vision and execution behind that mission. EKG is a rich, noisy, deeply temporal signal — extracting clinically meaningful predictions from single-lead consumer hardware is a genuinely hard problem, and we're solving it with 1.5M patient EHR records, an active FDA approval process, and backing from a16z and Mayo Clinic. You'll set the direction for how we do that, and lead the team that makes it real. What You'll Do Define and own ElectroKare's ML research agenda — architecture decisions, modeling philosophy, and the scientific roadmap from current models to clinical-grade predictions Lead and grow a team of ML engineers and researchers working on EKG waveform modeling and clinical datasets Make high-judgment calls on sequence architecture trade-offs, including state space models like Mamba, for long physiological time series Partner with clinical, product, and regulatory to translate hard healthcare problems into tractable ML ones — and keep one eye on the path to FDA validation Represent the science externally: with investors, clinical partners, and the broader research community What We're Looking For Proven leadership in applied ML/DL research, with the credibility to set direction and the depth to stay close to the work Strong intuition for architecture trade-offs on complex, temporal, real-world data Familiarity with state space models (Mamba) and modern sequence modeling Experience with clinical or biomedical datasets — you understand what it means for a model to be clinically meaningful, not just accurate MS or PhD in a relevant field, or equivalent industry depth; this is a senior leadership role Genuine passion for building things that improve patient outcomes at scale Nice to Have Background from research-grade ML environments such as Tempus, Isomorphic Labs, DeepMind, OpenAI, or Viz.ai Experience navigating FDA or other regulatory contexts for ML-based medical devices Signal processing or physiological time-series expertise Compensation The base pay range for this role is $200,000 - $250,000 per year.