About Cyngn, Inc. Based in Mountain View, CA, Cyngn is a publicly-traded autonomous technology company. We deploy self-driving industrial vehicles - specifically autonomous tuggers - to factories, warehouses, and other facilities throughout North America. Backed by a16z.
About the role
W e may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
What they're looking for
- Experience with IoT platforms, robotics frameworks (e.g., ROS), or autonomous vehicle technologies
- Solid understanding of network protocols and communication standards relevant to IoT and autonomous systems
- Knowledge of AMQP, MQTT, DDS, or other IoT-specific communication protocols
- Experience with time-series databases (e.g., InfluxDB, TimescaleDB) for handling large volumes of sensor data
- Familiarity with edge computing and fog architectures
- Experience with real-time operating systems and embedded software development
More about this role
About the role
- As the Staff Software Engineer for our SaaS platform team, you will be crucial in developing Cyngn's cutting-edge fleet management system for autonomous industrial vehicles. You'll collaborate with product and engineering teams to design, implement, deploy, and maintain a robust cloud-based solution that enables real-time control and monitoring of autonomous vehicles in the field. Your expertise will be instrumental in creating a scalable, high-performance system that empowers our customers to optimize their automated workflows and maximize operational efficiency.
What you'll do
- Architect and lead the development of a sophisticated, cloud-native fleet management system capable of real-time control and monitoring of numerous autonomous vehicles
- Design and implement scalable, distributed systems that can handle high-volume, real-time data processing and decision-making
- Develop robust APIs and microservices to support integration with various autonomous vehicle platforms and customer systems
- Create efficient algorithms for route optimization, task scheduling, and resource allocation across vehicle fleets
- Implement advanced data analytics and machine...
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