Edge AI Vision Engineer – Full-Stack & Cloud

Ford; Palo Alto, Northern (CA, KY); Hybrid; USD 85,000 - 193,000; Full time

Benefits offered by this job

Visa sponsorship provided

Relocation assistance

Medical, dental, vision coverage

Paid time off

Employee resource groups

Job summary

Ford is seeking a seasoned Full-Stack Software Engineer in the US to build the software ecosystem powering AI Vision Systems. You will bridge edge ML models with Google Cloud analytics, designing scalable RESTful APIs, and creating high-performance dashboards.

You’ll work across edge deployment, cloud backends, and web interfaces, using Python, React, and containerized deployments with Docker/Kubernetes, in a fast-paced production environment.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 3+ years of professional software engineering experience in production.
• Experience deploying to edge devices and cloud backends.

Responsibilities

• Deploy ML models to edge devices (NVIDIA Jetson/Thor) with low latency.
• Develop RESTful APIs and microservices for edge-to-cloud communication.
• Design data pipelines using Google Cloud tools for real-time data.
• Build dashboards with React/TypeScript for system health visualization.
• Collaborate with Data Scientists to containerize models with Docker/Kubernetes.
• Validate performance on factory floor with hardware engineers.

Skills

Edge development

Python

C++

Go

Node.js

GCP

React

Docker

CI/CD

Git

Education

Bachelor's degree in CS or related field

Tools

Docker

Kubernetes

OpenCV

TensorRT

OpenVINO

PyTorch

TensorFlow

MQTT

WebSockets

Job description

Ford is seeking a seasoned Full-Stack Software Engineer in the US to build the software ecosystem powering AI Vision Systems. You will bridge edge ML models with Google Cloud analytics, designing scalable RESTful APIs, and creating high-performance dashboards.

You’ll work across edge deployment, cloud backends, and web interfaces, using Python, React, and containerized deployments with Docker/Kubernetes, in a fast-paced production environment.