Senior Embedded Systems Engineer

present of AI; Winnipeg; Presencial; CAD 120.000 - 170.000; Jornada completa

Descripción de la vacante

present of AI seeks an engineering leader for an Android-based device used behind TVs in bars and restaurants. You will own software from platform builds to kernel drivers and multimedia paths, shipping features that ensure low-latency AI on embedded hardware.

The role requires deep AOSP/Linux kernel work on ARM, HDMI and multimedia debugging, and hands-on coding alongside mentoring duties. You will help shape architecture and performance while solving hardware-specific challenges in the field.

Formación

• Shipped a physical product in a related field.
• Deep experience with AOSP and the Linux kernel on ARM.
• Ability to debug multimedia and HDMI issues that appear on specific TVs/cable boxes.

Responsabilidades

• Own software on an Android device from platform build to kernel drivers and media paths.
• Set technical direction and mentor engineers while staying hands-on in code.
• Debug and optimize the multimedia pipeline for low latency and reliability.

Conocimientos

AOSP

Linux kernel

ARM

Multimedia debugging

Mentoring

Herramientas

HDMI

Board bring up

Video pipeline

Descripción del empleo

This role owns the software on an Android device installed behind TVs in bars and restaurants, from the platform build down to kernel drivers and the video and audio paths. A strong candidate has shipped a physical product, worked deeply in AOSP and the Linux kernel on ARM chips, and can debug multimedia and HDMI problems that only appear on certain TVs and cable boxes. The person also sets technical direction and mentors other engineers while staying hands on in the code.

How it fits the AI era

The on-device AI depends on a clean, low latency video and audio pipeline, so this engineer keeps the hardware and platform healthy enough for the models to run well. Much of the work is physical and messy, such as board bring up, HDMI quirks and remote recovery of devices in the field, and that stays human. AI can help with log analysis and routine debugging, but the judgment calls on architecture and hardware behavior remain with the engineer.

How it builds AI experience

The role offers hands on exposure to running models on embedded hardware, since the posting lists NPU or GPU acceleration as a nice to have and the AI runs on the box itself. A candidate can build this by learning how inference is deployed on ARM devices and how video frames move from capture to model input. Understanding the latency and resource limits of on-device AI is the practical way to prepare.

Worth showing

• AOSP platform changes shipped
• Linux kernel driver work
• ARM board bring up
• HDMI and AV debugging
• Multimedia pipeline latency tuning

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Taiv

An AI system that watches the live TV feed in bars and restaurants and swaps ad breaks for venue content and targeted ads, with the venue sharing the revenue.