Industrial AI Vision Engineer — Edge ML

Hemlock Semiconductor Group; Michigan; On-site; USD 90,000 - 124,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Disability benefits

PTO

Job summary

Hemlock Semiconductor Group in Michigan is seeking an AI Vision Machine Learning Engineer to design and implement advanced analytical models for static images and video within our manufacturing environment. You will develop models for object detection, measurement, and anomaly identification to deliver measurable business value.

You will deploy models to edge devices and integrate with cloud and factory systems, collaborate with process engineering, and report performance using BI tools such as

Qualifications

• BS/MS/PhD in computer science, data science, or engineering (master’s preferred).
• 3–5 years in computer vision, image analytics, or related fields in manufacturing.
• Proven production deployment of ML models; strong BI tooling experience.

Responsibilities

• Develop, train and refine DL models for object detection, classification and measurement.
• Deploy models to edge devices (Jetson, PLCs, cameras) and integrate with factory systems.
• Leverage cloud infra (Azure) for training, governance and data availability.
• Report model performance with BI tools; support production readiness and retraining.

Skills

Computer vision

OpenCV

TensorFlow

PyTorch

Python

C++/C#

Edge deployment

BI tools

Manufacturing domain

Storytelling / communication

Education

BS, MS, or PhD in computer science / data science / engineering

Tools

NVIDIA Jetson

Industrial PCs

PLCs

Smart cameras

GitHub / DevOps

Azure Foundry

Job description

Hemlock Semiconductor Group in Michigan is seeking an AI Vision Machine Learning Engineer to design and implement advanced analytical models for static images and video within our manufacturing environment. You will develop models for object detection, measurement, and anomaly identification to deliver measurable business value.

You will deploy models to edge devices and integrate with cloud and factory systems, collaborate with process engineering, and report performance using BI tools such as