Embedded Software Engineer

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Embedded Software Engineer

We are seeking an Embedded Software Engineer with strong Embedded Linux experience to join our engineering team. You will design, build, and maintain the software that powers our NVIDIA Jetson–based edge AI cameras — including Python application code, system services, OTA update mechanisms, networking, and device reliability.

This is a hands-on engineering role focused on Linux systems and product software running on resource-constrained devices. You will not be working on MCU firmware or low-level hardware bring-up. Instead, you’ll operate across the OS and application stack to ensure our camera systems are robust, secure, and easy to deploy at scale.

If you enjoy building software for real hardware, solving complex debugging challenges, and owning features end-to-end, we would love to speak with you!

What You Will Work On

  • Develop and maintain system-level and application-level software for NVIDIA Jetson devices
  • Implement and own OTA for our deployed device fleet
  • Write Python application code for device control, edge logic, monitoring, and data flows
  • Work with C/C++ components for performance-critical functionality
  • Integrate camera/video pipelines to capture, process, and analyze real-time video streams
  • Debug Linux systems involving multiple services, containers, and custom applications
  • Tune performance across the stack: kernel, services, containers, and user applications
  • Use Docker containers for packaging and deploying edge software components
  • Collaborate with hardware vendors to diagnose and resolve system-level issues
  • Work with backend/API teams to maintain reliable device–server communication

Qualifications

  • Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field
  • 5+ years of experience in Linux-based embedded systems or systems software
  • 3+ years of Python development experience
  • Solid C++ skills in a Linux environment
  • Experience with SBC or Embedded Linux platforms
  • Understanding of networking fundamentals (TCP/IP, routing, TLS/HTTPS, certificates)
  • Experience debugging Linux applications and services (systemd, logs, containers)
  • Strong problem-solving skills and an independent ownership mindset
  • Clear communication and collaboration skills

Nice to Have

  • Experience implementing OTA systems or device-update workflows
  • Experience with Docker containerization
  • NodeRED, Flask, or REST API development
  • Industrial automation background (PLC ladder logic, Structured Text)
  • Industrial protocols: EtherNet/IP, Profinet, Modbus, RS232, RS485, CANbus
  • Experience with OpenCV, GStreamer, or real-time video processing
  • Experience with FTP/SFTP/SMB, NTP synchronization, or device-to-server messaging
  • Experience with fleet management of edge devices

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Interview process

Step 1: Recruiter Screen - A 30-45 minute introductory call to discuss your background, your career goals, and what we’re building here.

Step 2: Technical Interview - A deep dive into your technical decision-making. This is a conversational interview (no live coding required) focused on how you solve complex problems.

Step 3: Live Coding Interview - An interactive session with two members of our engineering team. You’ll work through a real-world coding challenge together to demonstrate your hands-on development style.

Step 4: Onsite Interview - We’ll invite you to our office for a final round. This includes a hands-on trial with our actual product and a series of team fit conversations to ensure our values and culture align.

1
Yêu cầu 5 năm kinh nghiệm
1,500,000 ~ 2,500,000 TWD / năm
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Về chúng tôi

About Overview.ai

Overview.ai is bringing the cutting edge of AI computer vision to manufacturing—solving inspection problems that were previously not solvable with traditional machine vision. We’re a full-stack company: we deploy GPU-powered cameras on production lines, run inference on the edge, and operate a platform that supports large fleets of devices deployed across the world.

We're growing extremely fast. Our customers love the product because it works—high accuracy, fast deployment, and an operator-friendly experience that makes real factory rollouts possible (not just pilots).