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 ...
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 ...
Edge Solutions Architect
Troy, MI · On-site
$59.75 - $78.75/hr
... OpenVINO, ONNX Runtime, vendor SDKs). * Business Acumen: Ability to translate complex technical solutions into clear business value and ROI for executives. * Ability to design end-to-end Edge ...
New
Edge Solutions Architect
Troy, MI · On-site
$59.75 - $78.75/hr
... OpenVINO, ONNX Runtime, vendor SDKs). * Business Acumen: Ability to translate complex technical solutions into clear business value and ROI for executives. * Ability to design end-to-end Edge ...
New
Edge Solutions Architect
Troy, MI · On-site
$140 - $190/hr
... OpenVINO, ONNX Runtime, vendor SDKs)). * Business Acumen: Ability to translate complex technical solutions into clear business value and ROI for executives. Ability to design end‑to‑end Edge ...
New
Edge Solutions Architect
Troy, MI · On-site
$140 - $190/hr
... OpenVINO, ONNX Runtime, vendor SDKs)). * Business Acumen: Ability to translate complex technical solutions into clear business value and ROI for executives. Ability to design end‑to‑end Edge ...
New
Openvino information
What is OpenVINO?
OpenVINO (Open Visual Inference and Neural Network Optimization) is a free toolkit developed by Intel to help developers optimize and deploy AI inference, particularly deep learning models, across Intel hardware such as CPUs, GPUs, VPUs, and FPGAs. It is mainly used for accelerating computer vision applications like image classification, object detection, and facial recognition. OpenVINO streamlines the process of converting and optimizing models from popular frameworks, making them faster and more efficient for edge and cloud deployments.
What skills and qualifications are needed to work with OpenVINO?
To thrive as an OpenVINO Developer, you need a solid background in computer vision, deep learning, and proficiency in Python or C++, often supported by a degree in computer science or a related field. Familiarity with the OpenVINO toolkit, neural network optimization, and frameworks like TensorFlow or PyTorch is essential. Strong problem-solving skills, attention to detail, and effective communication help developers collaborate and innovate in deploying AI solutions. These skills ensure optimized AI performance on edge devices and successful integration of machine learning models into production environments.
What challenges do professionals face when deploying AI models to edge devices using OpenVINO?
Professionals working with OpenVINO often encounter challenges related to optimizing and converting AI models to ensure they run efficiently on diverse edge hardware. These challenges include ensuring compatibility with various device architectures, minimizing inference latency, and handling limitations in memory and compute resources. Additionally, troubleshooting model conversion errors and maintaining accuracy during optimization are frequent tasks. Collaboration with hardware engineers and software developers is also essential to address performance bottlenecks and integrate solutions smoothly into production environments.
What is the difference between Openvino vs Computer Vision Engineer?
| Aspect | Openvino | Computer Vision Engineer |
|---|---|---|
| Required Credentials | Knowledge of AI frameworks, hardware optimization, programming skills | Degree in Computer Science, Electrical Engineering, or related fields; experience in AI and image processing |
| Work Environment | Tech companies, AI development labs, hardware manufacturers | Research institutions, tech firms, startups, or industry-specific companies |
| Employer & Industry Usage | Primarily used in AI inference optimization, embedded systems, and hardware acceleration | Developing and implementing computer vision algorithms for applications like surveillance, robotics, and autonomous vehicles |
Openvino focuses on optimizing AI inference workloads and hardware acceleration, often requiring knowledge of AI frameworks and hardware. In contrast, a Computer Vision Engineer designs and develops vision algorithms, working across various industries. While both roles involve AI and image processing, Openvino is more specialized in deployment and optimization, whereas Computer Vision Engineers focus on algorithm development and application.
What are popular job titles related to Openvino jobs in Michigan?
For Openvino jobs in Michigan, the most frequently searched job titles are:
- Remote Tvm
- Associate Solutions Architect
- Machine Learning Engineer Apprenticeship
- Machine Learning Engineer New Grad
- Senior Machine Learning Researcher
- Machine Learning Engineer Intern
- Google Cloud Machine Learning Engineer
- Junior Machine Learning Engineer
- Embedded Machine Learning Engineer
- Remote Machine Learning Engineer
What job categories do people searching Openvino jobs in Michigan look for?
The top searched job categories for Openvino jobs in Michigan are:
What cities in Michigan are hiring for Openvino jobs?
Cities in Michigan with the most Openvino job openings:
Software Engineer
Redford, MI
Ford Motor Company •
Motor Vehicle Manufacturing • 10K+ employees10,000+ employees
7.6
Based on 525 frontline employees who took The Breakroom Quiz
13th of 45 rated automakers
People enjoy working here
Good employer
Recommended by students
Paid breaks
Respectful managers
Full-time
Re-posted 7 days ago
Job description
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.
Required Qualifications:
- 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 Node.js).
- 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 using docker as the key configuration, build, and deploy mechanism, CI/CD pipelines and disciplined version control approach (GIT based)
Desired 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.
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.
- 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.
About Ford Motor Company
Sourced by ZipRecruiter
Industry
Motor vehicle manufacturing and trucking
Company size
10,000+ Employees
Headquarters location
Dearborn, MI, US
Website
What Ford Motor Company employees say
Pay
Benefits
Hours and flexibility
Workplace
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