About the Role

We are looking for an Embedded Systems Engineer to help develop the next generation of low-power, AI-enabled consumer devices. You will work across firmware, real-time processing, and embedded ML deployment on modern ultra-low power edge-AI platforms. This role involves building firmware for multi-sensor, multi-microphone systems and collaborating closely with hardware teams to create tightly integrated products.

Key Responsibilities

• Develop and optimize firmware for edge-AI embedded platforms.
• Implement real-time processing pipelines for sensor, audio, and wireless subsystems.
• Integrate and optimize ML/AI models for resource-constrained hardware.
• Collaborate with hardware teams during board bring-up, driver development, and system validation.
• Development of embedded test infrastructures and data-collection frameworks.
• Contribute to prototyping of new form-factor devices in the wearable domain.

Preferred Skills & Experience

• Strong C/C++ for embedded systems; Python for tooling and automation.
• Experience with ARM microcontrollers or processors; familiarity with DSP or NPU acceleration.
• Knowledge of real-time operating constraints and embedded communication protocols.
• Experience debugging at the firmware–hardware boundary.
• Understanding of audio, sensor fusion, or low-latency processing is a strong plus.
• Experience with embedded ML frameworks (e.g., TFLM, CMSIS-NN).
• Experience with ML deployment tools on resource-constrained devices (TFLite, ONNXRuntime, ExecuTorch,...)
• Familiarity with compact consumer-electronics design practices.
• Interest in wearables, audio technologies, or multimodal sensing.

Sent CVs to hr@hearvana.ai

Salary range: 90-110k