Embedded Firmware Engineer, Wearable Neural Interface

Noïa Labs; Paris; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

Noïa Labs is seeking an experienced Embedded Software Engineer in Paris (hybrid) to develop software for a non-invasive neural interface. You will work across firmware and hardware, tackling real-time data acquisition with strict latency, power, and reliability constraints.

The role involves firmware architecture, sensor data handling, device communication, hardware bring-up, testing, and collaboration with ML and product teams in a fast-moving startup environment.

Qualifications

• 5+ years of experience in embedded software, firmware engineering, or a related field.
• Strong experience writing reliable embedded software in C, C++, or Rust.
• Experience with microcontrollers, bare-metal systems, RTOS, or embedded Linux.
• Experience developing firmware for battery-powered or resource-constrained embedded systems.
• Experience with BLE, Wi‑Fi, USB, SPI, I2C, UART, or other device communications protocols.
• Experience debugging firmware and hardware issues with lab equipment.
• Strong ownership, practical problem-solving skills, and attention to detail.

Responsibilities

• Design, implement, and validate embedded software for our wearable neural interface.
• Develop firmware for sensor acquisition, timing, buffering, and communication.
• Bring up, debug, and validate hardware prototypes with the electronics team.
• Optimize embedded systems for latency, power, reliability, and signal quality.
• Build tools and tests to validate device behavior and data quality.
• Work with infra and ML teams to stream neural data reliably into the platform.
• Work with suppliers and manufacturers to turn prototypes into products.

Skills

Embedded software

C/C++ or Rust

RTOS / Embedded Linux

BLE/Wi‑Fi/USB

Lab debugging

Ownership mindset

Job description

Noïa Labs is seeking an experienced Embedded Software Engineer in Paris (hybrid) to develop software for a non-invasive neural interface. You will work across firmware and hardware, tackling real-time data acquisition with strict latency, power, and reliability constraints.

The role involves firmware architecture, sensor data handling, device communication, hardware bring-up, testing, and collaboration with ML and product teams in a fast-moving startup environment.