Overview is a company that takes the cutting edge in computer vision and deep learning and applies it to previously unsolvable manufacturing inspection problems. We are truly a full stack company. We install physical cameras into the facility, run inference on the edge and manage massive deployments. Overview also streams gigabytes of video/image data to the cloud for our web platform to give customers advanced insights and analytics.

We are looking for engineers who like to solve tough challenges across the stack. This might include wrangling 500mb images or deploying optimized models in one click that can handle 10 parts a second. We are looking for people who are dynamic, who are excited to work on a different challenge every week, whether it's the final inspection on a medical device or making sure a razor blade has a perfect edge.

Company Overview

Overview.ai is a leading innovator in next-generation computer vision technology for complex manufacturing. Our smart camera is revolutionizing manufacturing efficiency and quality, backed by top-tier investors. This is an opportunity to join a team that’s not only impacting the industrial vision technology sector but also shaping global manufacturing standards.

Job Description

We are seeking a detail-oriented and experienced Embedded Software Engineer to join our team. The ideal candidate will be responsible for designing and building production software for an embedded AI camera product and working with low-level OS, containerization, and hardware. At Overview, you would be working on problems such as optimizing an OS for lower jitter, developing high-impact features for our customers, and improving overall product reliability. If you like working on things like designing a framework for delta updates in the field, or working with bits and bytes at the hardware level, we’d love to talk to you.

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Job Location

San Francisco, CA, United States (hyrbid - 3 days per week in office)

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Years of Experience

Candidates should have 3-5 years of relevant experience in the field.

Responsibilities

• As an Embedded Software Engineer, you will take ownership of ensuring rapid delivery of high-quality bug-free products and features to our customers on our Jetson Linux system.
• Work directly on our device client code that sits on the Nvidia Jetson.
• Interface directly with hardware vendors to identify root cause issues and resolutions.
• Work on interfaces for device I/O with factory systems like PLC's.
• Manage and develop an OTA deployment framework for a fleet of cameras in the field.
• Improve reliability of the camera system, from file system reliability to network socket resilience.

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Required Skills

• Experience with Linux SBCs such as Raspberry Pis or NVIDIA Jetsons.
• Experience writing production software for an embedded system in Python, Docker.
• Familiarity with PLC usage and protocols and hardware debugging.
• Experience troubleshooting and analyzing remotely deployed software systems.
• Familiarity with electronics, wiring, and troubleshooting.
• Experience with command line interfaces, shell scripting, and scripting languages
  (Python, JavaScript).

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Qualifications

• 3-5 years of experience in software engineering, or embedded engineering.
• Proven abilities in delivering production software on an embedded Linux system.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork abilities.

How to Apply

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**Interested candidates are encouraged to submit their resume and a cover letter through our careers page. We look forward to discovering how your expertise can contribute to the success of Overview

Overview's tech is far reaching. We deploy highly reliable camera hardware and GPU's into manufacturing and industrial settings. We have an IoT fleet management stack to update, secure, and manage our fleet of devices. We stream this data to our cloud or to a customers hybrid cloud where we have a user facing platform where customers can interact with their devices, deploy new deep learning models, and see advanced analytics.

We use Docker to deploy web infrastructure and deep learning models. We have an extensive deep learning stack using Tensorflow, PyTorch and packaged with Onnx. Our frontend is in React, which is updated in real time from our fleet using MQTT. And the list goes on...