Software Engineer, AI Engineer, Machine Learning/ ML Engineer
Job in
Redford, Wayne County, Michigan, 48239, USA
Listed on 2026-05-22
Listing for:
Ford Motor Company
Full Time
position Listed on 2026-05-22
Job specializations:
-
Software Development
AI Engineer, Machine Learning/ ML Engineer, Software Engineer, Data Scientist
Job Description & How to Apply Below
We are seeking an experienced Full-Stack Software Engineer to build the software ecosystem powering our next-generation AI Vision Systems.
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 (Big Query, Postgres) to handle real-time image/video data and model telemetry.
* Web Interfaces:
Create intuitive, high-performance web-based dashboards (React/Type Script) 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.
* Incremental and Iterative Delivery:
Work with the team and key stakeholders to find and deliver product increments in an iterative way, taking reasonable risks, validating key hypothesis, and learning continuously
* Cross-Functional Deployment:
Collaborate with Data Scientists to containerize models (Docker/Kubernetes) and with Hardware Engineers to validate performance on the factory floor.
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 (Big Query, Postgres) to handle real-time image/video data and model telemetry.
* Web Interfaces:
Create intuitive, high-performance web-based dashboards (React/Type Script) 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.
* Incremental and Iterative Delivery:
Work with the team and key stakeholders to find and deliver product increments in an iterative way, taking reasonable risks, validating key hypothesis, and learning continuously
* Cross-Functional Deployment:
Collaborate with Data Scientists to containerize models (Docker/Kubernetes) and with Hardware Engineers to validate performance on the factory floor.
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