05 Aug
|
Doist
|
New South Wales
05 Aug
Doist
New South Wales
At the heart of this role is our embedded Linux Edge AI sensor platform.You will help shape how our devices are built, provisioned, secured, updated and supported throughout their lifecycle.
Your work will extend across embedded software, hardware integration, Edge AI, audio processing, device deployment and the cloud services supporting our deployed fleet.This is not a narrow software role.You will work closely with hardware, electronics, AI, cloud and manufacturing specialists to solve complex engineering problems and turn emerging technologies into dependable, field-ready products.You do not need to be the deepest specialist in every area.
You will, however, need the engineering judgement, curiosity and adaptability to move between disciplines and improve the reliability of the complete system.
What you will be working on:
Own and continuously improve our embedded Linux platform, including Yocto builds, boot configuration, device trees, kernel changes, drivers and system services.
Improve build, release, provisioning, flashing, diagnostics and over-the-air update processes.
Develop more secure and repeatable workflows for deploying, maintaining and recovering connected devices.
Integrate and troubleshoot cameras, microphones, cellular modems and environmental sensors.
Work across hardware interfaces including I2C, SPI, UART, CSI, USB and PCIe.
Strengthen device security through OS hardening, secure boot,
improved key management and vulnerability management.
Profile and optimise embedded machine-learning inference and computer‐vision features within device power, compute and bandwidth constraints.
Support quantisation, NPU integration and power‐aware Edge AI runtime improvements.
Enhance audio‐analysis capabilities, including event detection, classification, direction of arrival and multimodal detection.
Contribute to backend services, APIs, data pipelines and internal tools supporting our deployed sensor fleet.
Improve fleet diagnostics, observability and operational reliability.
Work closely with a small multidisciplinary team from early concept through to manufacturing and field deployment.
We will help you create a platform where:
Devices can be built, provisioned, updated and recovered through secure, repeatable processes.
Edge AI, computer vision and audio‐analysis features perform reliably within real‐world hardware constraints.
Recent cameras, modems, microphones and sensors can be integrated without fragile one‐off solutions.
Device issues can be diagnosed and resolved effectively across a deployed fleet.
Data is reliably ingested, processed and stored through observable cloud services.
Engineering decisions consider the entire product lifecycle, from development and manufacturing to deployment and long‐term operation.
#J-*****-Ljbffr
📌 Senior Embedded Linux Software Engineer – Edge Ai & Iot (New South Wales)
🏢 Doist
📍 New South Wales