Work evidence

Senior R&D Engineer

Led technical work across wearable hardware, sensor integration, home/clinical data workflows, reliability, ML validation, and regulated documentation.

Rhaeos, Inc. · May 2022 – Dec 2025

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Role focusSenior R&D Engineer supporting wearable medical devices, FlowSense Clinical/Home, hydrocephalus shunt-flow assessment, algorithm/ML pipelines, wound monitoring, FDA-ready documentation, manufacturing/reliability, and clinical/preclinical studies.
Projects3 documented projects

Responsibilities

What this role covered.

  • Supported FlowSense Clinical / ACE, FlowSense Home / Lynx, and Wound Monitoring Platform / Tabby development.
  • Integrated sensors, electronics, packaging, adhesives, Qi charging, motion sensing, onboard memory, and data workflows.
  • Built validation workflows across bench testing, clinical/home monitoring, preclinical studies, data review, and deployment checks.
  • Created FDA-ready engineering documentation including requirements, test protocols, assembly procedures, inspection records, BOMs, DMFEA, and design notes.
  • Worked across hardware, firmware, software, clinical, regulatory, manufacturing, supplier, patient, and caregiver feedback loops.

Achievements

Evidence from the work.

  • Improved FlowSense Home field reliability from about 70% in Gen 1 to about 96% by the final Gen 3 clinical study.
  • Led 20–30 clinical-study device builds and reduced build cycles from about 6 weeks to about 3 weeks.
  • Advanced FlowSense Home across 3 design generations, 100+ manufactured units, 200+ participants, and 2,800+ home-device wear hours.
  • Supported 3,000+ hours of physiological/device data and 200+ HA Connect datasets.
  • Built DSP/ML workflows spanning ingestion, labeling, QC, dataset versioning, feature generation, validation, bias checks, explainability, and deployment checks.
  • Helped improve FlowSense clinical algorithm performance from a 74% baseline to 0.81 AUC / 82% accuracy in blinded clinical validation.
  • Led NIH R43 Phase I wound-sensing work from concept to study-ready device and grant deliverables in about 1 year.

Technical range

Tools, systems, and engineering areas.

Medical devicesWearable sensingFlowSenseAlgorithm validationReliabilitySensor integrationAdhesives and skin interfaceQi chargingBLE / NFCManufacturing readinessFDA-ready documentationPhysiological ML

Related projects

Projects completed within this role.

Medical devices

FlowSense Clinical / ACE

Clinical wearable and DSP/ML workflow for noninvasive CSF shunt-flow assessment; improved from a 74% baseline to 0.81 AUC / 82% blinded validation accuracy.

Medical devices

FlowSense Home / Lynx

Home-use hydrocephalus wearable advanced across 3 design generations, 100+ units, 200+ participants, 2,800+ wear hours, and 70% → 96% reliability improvement.

Medical devices

Wound Monitoring Platform / Tabby

NIH R43 Phase I multimodal wound patch with thermal/humidity/temperature sensing, 40 mAh battery, 20-subject dataset, 172 logs, and 5-fold wound-model validation.