Developing ultra-high-bandwidth wearable biosensors and a digital health mainframe, connecting humans, physiological data, and artificial intelligence health analytics in real time

We are looking for exceptional engineers and scientists. No medical background is required — talent and drive matter far more. We expect most of our team to come from other areas and industries.

We are primarily looking for evidence of exceptional ability and a track record of building things that work. Send a GitHub, paper, or a one-page writeup of something you built.

Remote work is acceptable, and you are always welcome to our labs around the planet Earth (Milky Way Galaxy, Orion Arm).

If you don’t see a role that fits but believe you can meaningfully contribute, reach out to us at team@cardio-group.com.

P.S.
If this page feels strangely familiar — you’re not imagining it. Builders recognize builders. E.M., if you’re reading this: our inbox is open, same obsession with first principles. Different problem.
R&D Engineer, Microoptics & Biosensors

Invent sensing that changes what’s measurable — then make it real in a wearable. Lead experiments, prototypes, and integration of microoptics/biosensing into robust, manufacturable systems that survive the real world. Focus: microoptics • biosensors • experimental design • prototyping • system integration


R&D Engineer, Sensor Systems

Turn messy physics into clean signals at scale. Build and iterate sensing architectures, test methodologies, and bench‑to‑wearable transitions — from first principles to repeatable performance. Focus: sensing R&D • signal quality • test methods • instrumentation • iteration speed


Hardware Systems Engineer, Wearables

Own the end‑to‑end hardware system — not just a component. Define interfaces, budgets (power/thermal/signal), verification strategy, and cross‑team alignment so the wearable behaves like a single coherent machine. Focus: system architecture • interface definition • requirements • verification • tradeoffs


Electrical Engineer

Build wearable electronics that deliver pristine data on a tiny power budget. Design sensor front‑ends, power systems, and PCBs — partnering with firmware to maximize robustness, battery life, and signal fidelity. Focus: PCB • power • sensors • validation • signal integrity


RF & Antenna Engineer (BLE / Wearables)

Make wireless work on the human body — reliably, globally, and at scale. Own RF performance, antenna design, tuning, coexistence, and pre‑compliance strategies for wearable constraints. Focus: BLE/RF • antenna design • tuning • EMC pre‑compliance • reliability


Software Engineer, Embedded Systems & Firmware

Ship firmware that makes the wearable feel effortless — and the data trustworthy. Build BLE connectivity, sensor scheduling, low‑power operation, and on‑device processing that survives edge cases and real users. Focus: BLE • low power • sensors • reliability • embedded architecture


Mechanical Engineer

Design the wearable’s physical truth: comfort, sealing, durability, and manufacturability. Own enclosure/strap mechanisms, environmental protection, and DFM/DFA from prototype to production. Focus: CAD • DFM/DFA • sealing • durability • prototyping


Microelectronics Packaging Engineer

Make advanced sensing manufacturable — with yield and reliability you can bet the product on. Own packaging strategy across thermal/mechanical constraints, assembly methods, and environmental stress performance. Focus: packaging • reliability • assembly constraints • yield • process development


CNC Machinist

Build the precision hardware that accelerates every iteration. Prototype and produce tight‑tolerance parts for tooling, fixtures, and test rigs — owning setup, quality checks, and speed of iteration with engineering. Focus: CNC setup • tight tolerances • prototype iteration • fixtures • quality checks


Data Scientist

Turn raw physiology into insights you can defend with evidence. Define metrics, analyze cohorts, design experiments, and partner with engineering to validate signal quality and product outcomes. Focus: metrics • experimentation • statistical rigor • analytics • dataset curation


Software Engineer, Machine Learning (Supervised AI)

Ship supervised ML that works in production — measurable, monitored, and improving. Build training pipelines, feature systems, evaluation, deployment, and model monitoring for health analytics at scale. Focus: supervised ML • training pipelines • evaluation • deployment • monitoring