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.

ABOUT THE COMPANY

Overview, with its cutting-edge AI, aims to enhance factory efficiency and maintain America's manufacturing edge. Their OV20i smart camera utilizes the latest in vision transformer and edge GPU technology for improved quality control and efficiency in manufacturing. The company, inspired by its founders' experience at Tesla, is the answer to the industrial market’s need for easy-to-deploy inspection systems.

ABOUT THE ROLE

As a Senior Applications Engineer, you will play a crucial role in supporting clients as they install and integrate Overview's cameras with PLC systems, focusing on Allen Bradley and Siemens platforms. There is an opportunity for significant customer travel (up to 50%). You’ll be honing a wide variety of manufacturing skills ranging from mechanical to PLC programming and of course, vision implementation.

WHAT YOU WILL BE DOING

• Client Assistance in System Installation
• Provide hands-on assistance to clients with the installation of Overview's vision systems.
• Guide clients through configuration and customization processes.
• Perform testing and validation to ensure systems meet performance standards.
• Integration with PLC Systems
• Assist clients in integrating Overview's cameras with PLC systems, especially Allen Bradley and Siemens.
• Offer expertise in establishing seamless connections between vision systems and PLC infrastructure.
• Address and resolve integration challenges, providing effective solutions.
• Technical Support and Problem Solving
• Deliver ongoing technical support and resolve issues during and after installation.
• Collaborate with clients to solve complex technical problems.
• Ensure high levels of system functionality and client satisfaction.
• Training and Knowledge Transfer
• Train clients on system operation, maintenance, and best practices.
• Create and distribute training materials and documentation.
• Serve as a technical liaison for client inquiries.

WHAT WE WANT TO SEE

• Minimum of 3 years of experience in vision system installation and PLC integration, with a focus on Allen Bradley and Siemens.
• Willingness to travel up to 50% of the time, including international travel.
• Proficient in problem-solving, communication, and customer service.

*Overview provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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...