Get more replies from employers
Send a job-specific resume in minutes.
Med Clinic X, a healthcare technology company building digital health ecosystems, seeks a Firmware Engineer to design and optimize firmware for healthcare devices and IoT-enabled medical systems across the United States.
You will collaborate with hardware, embedded, and cloud teams to deliver low-level software powering connected devices, ensure secure communication with cloud platforms, and drive reliability in medical environments.
Med Clinic X is a healthcare technology company building advanced digital health ecosystems that combine software, AI, cloud platforms, and connected medical devices for healthcare organizations across the United States.
We develop healthcare SaaS platforms, AI-driven healthcare systems, patient portals, telemedicine solutions, automation workflows, and integrated medical device technologies that support real-world clinical environments.
Our mission is to build reliable, secure, and high-performance healthcare systems that extend into connected devices and real-time monitoring solutions.
We are seeking a Firmware Engineer to design, develop, and optimize firmware for healthcare devices and IoT-enabled medical systems.
In this role, you will build low-level software that powers connected healthcare devices and ensures seamless communication with cloud-based healthcare platforms used across the United States.
You will collaborate with hardware engineers, embedded developers, and cloud teams to build safe and reliable healthcare technologies.
At Med Clinic X, you will build the foundation of connected healthcare technology. You will:
C / C++ Programming Embedded Systems Programming Microcontrollers (ARM / STM32) Real-Time OS (FreeRTOS) IoT Protocols (MQTT / BLE) Hardware Debugging & JTAG
Build firmware for real-time patient vital sign monitors and smart sensors.
Design low-power microcontroller logic loops to ensure device longevity.
Configure high-frequency sample buffers and local sensor processing logic.
Synchronize raw device readings with cloud portals using secure transport links.
Expose interfaces on microcontrollers to trigger local tinyML algorithms.
Test hardware interactions with telemetry message queues and API layers.