ai is transforming manufacturing quality control with advanced edge-enabled AI vision system that combines cutting-edge deep learning with ease of use and quick setup. Our system handles a wide array of inspection tasks—from subtle assembly verification to defect detection and orientation checks—delivering real-time, high-accuracy inspections that seamlessly integrate into existing production lines.
Trusted by leading manufacturers like Ford, Honda, Toyota, SpaceX, Milliken, and Flex-N-Gate, our cameras enables faster throughput, reduced scrap, and lower inspection costs—without the complexity and expense of traditional vision systems.
We are seeking a Senior Embedded Systems 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.
Develop and maintain system-level and application-level software for reliability in the field for our edge AI 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
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
Mentor the team through code review, coaching, and general feedback
Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field
5-7+ years of experience in Linux-based embedded systems or systems software
Solid C++ skills in a Linux environment and/or Python development experience
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)
Experience with Docker containerization
Strong problem-solving skills and independent ownership mindset
Clear communication and collaboration skills
Experience implementing OTA systems or device-update workflows
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
Build core systems that directly impact real-world manufacturing
High ownership and autonomy
Work closely with hardware, AI, and customer-facing teams
Join a fast growing, fast moving and profitable startup
AI Machine Vision Systems for Manufacturing.
Deploy powerful automated inspection in days with Gen AI. Our vision systems ensure flawless quality control and find defects others miss.
Manufacturers across industries partner with us to achieve measurable results: 75% reduction in inspection costs, 50% reduction in rework, 100% defect coverage, and 20% reduction in scrap.
Why manufacturers choose Overview:
Our platform delivers state-of-the-art accuracy with industry-leading ease of use and maintainability. Unlike traditional machine vision, our AI-first architecture is designed for real production environments where conditions change, data is imperfect, and downtime isn't an option.
We understand manufacturing because we've lived it. Founded by former senior Tesla manufacturing leaders, our team brings deep expertise from scaling quality systems in the world's most demanding environments—experience that shaped everything from our rapid deployment capabilities to our tools that handle messy production data.
Global reach, dedicated support:
With teams across 10 countries, we provide white-glove support wherever you manufacture, from Silicon Valley to major production hubs across North America, Europe, and Asia-Pacific.
At Overview, we're not just shaping the future of AI—we're making it work where it matters most: on your factory floor.
