Embedded AI Firmware Engineer for Hearing Devices

Sonova; Schweiz; Hybrid; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Training opportunities

Career growth

Job summary

Sonova, a leading hearing care company headquartered in Switzerland, is seeking a Software Engineer Embedded AI to push the boundaries of on-device intelligence. You will develop firmware for a low-power AI platform and help shape our edge AI capabilities for next-generation hearing devices.

You will work with cross-functional teams to optimize AI software for latency and energy, translating research into production-ready features while maintaining code quality and documentation.

Qualifications

• Degree in Computer Science, Electrical Engineering, or a related technical field.
• Hands-on experience with embedded C++ and Python.
• Experience deploying neural networks on embedded systems.
• Familiarity with deployment frameworks such as TensorFlow Lite, ONNX, TVM, or ExecuTorch.
• Fluent English with strong written and verbal communication skills.

Responsibilities

• Develop firmware for a deeply embedded AI platform under strict latency, memory, compute, and energy constraints.
• Design, implement, and maintain the embedded AI software stack for production-ready features.
• Collaborate with AI and DSP experts to deploy DNNs in hearing-device applications.
• Tailor AI algorithms to the embedded platform constraints (quantization, memory, power).
• Implement prototypes and bring them to production, integrating with other engineering teams.

Skills

Embedded C++

Python

OO programming

English communication

Education

Degree in Computer Science or Electrical Engineering

Tools

TensorFlow Lite

ONNX

TVM

Job description

Sonova, a leading hearing care company headquartered in Switzerland, is seeking a Software Engineer Embedded AI to push the boundaries of on-device intelligence. You will develop firmware for a low-power AI platform and help shape our edge AI capabilities for next-generation hearing devices.

You will work with cross-functional teams to optimize AI software for latency and energy, translating research into production-ready features while maintaining code quality and documentation.