We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we’re all a part of something bigger than ourselves. Are you ready to change the way the world moves?
We are seeking an experienced Full-Stack Software Engineer to join our dynamic team working on building a cutting-edge Artificial Intelligence (AI) Vision System from the ground up. Utilizing a Google Cloud Platform (GCP) edge-to-cloud continuum, you will develop and maintain the software that powers image acquisition, serves machine learning models on edge PCs, and integrates with cloud-based APIs and infrastructure.
This is a hands-on role that bridges front-end, back-end, and edge computing. You will take end-to-end ownership of the software lifecycle—from architecture and development to edge deployment, telemetry monitoring, and ensuring high reliability in a live manufacturing environment.
What you'll do...
- Edge-to-Cloud Development: Build scalable, secure web-based interfaces, RESTful APIs, and microservices to interact with edge vision systems and manage cloud-based machine learning workflows on GCP.
- MLOps & Edge Computing: Deploy, optimize, and serve machine learning models on edge devices (e.g., industrial PCs, NVIDIA Jetson). Implement software solutions for low-latency image acquisition and real-time inference.
- Database Integration: Architect and manage data pipelines using SQL and NoSQL databases to handle large datasets, assembly traceability identifiers, and model result storage.
- Remote Device Management: Develop and establish monitoring, telemetry, and remote management tools for edge hardware and cameras to ensure system health and performance.
- Cross-Functional Collaboration: Partner with Data Scientists, Hardware Engineers, and Product Managers to translate business requirements into robust technical solutions.
- Code Quality & CI/CD: Write clean, maintainable code following DevSecOps standards. Implement unit/integration testing and manage containerized CI/CD pipelines to ensure reliable software delivery.
- Troubleshooting & Debugging: Diagnose and resolve complex system issues spanning edge computing performance, API integrations, and network connectivity on the manufacturing floor.
