Full-Stack Software Engineer AI Vision Systems (Edge & Cloud)
Job Location:
Job Location:
Dearborn, MI - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
2 hours ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
We are seeking an experienced Full-Stack Software Engineer to build the software ecosystem powering our next-generation AI Vision Systems. You will develop the connective tissue between high-performance machine learning models running on edge hardware and our Google Cloud-based analytics backend. This is a hands-on role for an engineer who is passionate about bringing AI out of the lab and into the real world.
Roles and Responsibilities:
Edge Software Integration: Develop and optimize software to deploy machine learning models on edge devices (NVIDIA Jetson/Thor) ensuring low-latency performance for real-time vision tasks.
Full-Stack API Development: Build scalable RESTful APIs and microservices (Python/C) that allow edge devices to communicate seamlessly with cloud backends.
Data Architecture: Design and manage data pipelines using Google Cloud tools (BigQuery Postgres) to handle real-time image/video data and model telemetry.
Web Interfaces: Create intuitive high-performance web-based dashboards (React/TypeScript) for monitoring system health and visualizing AI-driven insights.
AI-Augmented Engineering: Heavily leverage Agentic AI tools and LLM-assisted workflows to accelerate development cycles and maintain high code quality.
Cross-Functional Delivery: Collaborate with Data Scientists to containerize models (Docker/Kubernetes) and with Hardware Engineers to validate performance on the factory floor.
Required Skills:
Experience: 3 years of professional software engineering experience in a production environment.
Edge Development: Proven experience deploying software to edge computing hardware or IoT devices.
Backend Mastery: Strong proficiency in Python (required) and at least one other language (C Go or ).
Cloud Fluency: Experience building on Google Cloud Platform (GCP) or similar (AWS/Azure) specifically with managed database services.
Modern Frontend: Experience building responsive web applications with React or similar modern frameworks.
DevOps Basics: Familiarity with Docker CI/CD pipelines and version control (Git).
Preferred Skills:
Experience with OpenCV TensorRT or OpenVINO for vision optimization.
Familiarity with ML frameworks like PyTorch or TensorFlow.
Knowledge of industrial protocols (MQTT WebSockets) for real-time data streaming.
A passion for Agentic workflows and continuous improvement.
Roles and Responsibilities:
Edge Software Integration: Develop and optimize software to deploy machine learning models on edge devices (NVIDIA Jetson/Thor) ensuring low-latency performance for real-time vision tasks.
Full-Stack API Development: Build scalable RESTful APIs and microservices (Python/C) that allow edge devices to communicate seamlessly with cloud backends.
Data Architecture: Design and manage data pipelines using Google Cloud tools (BigQuery Postgres) to handle real-time image/video data and model telemetry.
Web Interfaces: Create intuitive high-performance web-based dashboards (React/TypeScript) for monitoring system health and visualizing AI-driven insights.
AI-Augmented Engineering: Heavily leverage Agentic AI tools and LLM-assisted workflows to accelerate development cycles and maintain high code quality.
Cross-Functional Delivery: Collaborate with Data Scientists to containerize models (Docker/Kubernetes) and with Hardware Engineers to validate performance on the factory floor.
Required Skills:
Experience: 3 years of professional software engineering experience in a production environment.
Edge Development: Proven experience deploying software to edge computing hardware or IoT devices.
Backend Mastery: Strong proficiency in Python (required) and at least one other language (C Go or ).
Cloud Fluency: Experience building on Google Cloud Platform (GCP) or similar (AWS/Azure) specifically with managed database services.
Modern Frontend: Experience building responsive web applications with React or similar modern frameworks.
DevOps Basics: Familiarity with Docker CI/CD pipelines and version control (Git).
Preferred Skills:
Experience with OpenCV TensorRT or OpenVINO for vision optimization.
Familiarity with ML frameworks like PyTorch or TensorFlow.
Knowledge of industrial protocols (MQTT WebSockets) for real-time data streaming.
A passion for Agentic workflows and continuous improvement.
