Industrial Vision Edge Developer

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
No Travel Required

Skills

Industrial Vision Edge

Job Details

Industrial Vision Edge Developer

Remote

12 months contract

Looking immediately (for now) for more of a platform developer (DevOps), but with experience in computer vision software, tools and analytics

CANDIDATES FROM BANKS, HOSPITALS AND HEALTHCARE. Not needed

Strongly prefer someone local (or reasonable driving distance to Georgetown, KY).

Will consider remote for a strong candidate, but must travel 2+ times a month. Reimbursement for travel as required.

Skills (EXPERT/ADVANCED/NONE):
Experience designing solutions for an industrial setting
Experience developing solutions, as described in Job Requirements
Design, train, and deploy real-time ML/CV models optimized for edge hardware
Implement DevOps/MLOps pipelines for edge deployment, updates, and rollback
Optimize inference performance (latency, throughput, memory, power) on industrial edge devices
Integrate vision systems with PLCs, MES, and factory networks
Questions (must reply YES to ALL):
Do you have experience with designing/developing computer vision solutions? (e.g. experience with Cognex, computer vision libraries, streaming video/image processing, etc.)
Do you have experience Implementing DevOps/MLOps pipelines for edge deployment, updates, and rollback?
Do you live within reasonable driving distance of Georgetown, KY? Or willing to relocate? Or willing to travel 2+ weeks/month?
Description:
We are seeking a Senior Industrial Vision Edge Developer to lead the design, deployment, and optimization of real-time computer vision systems at the edge for automotive manufacturing and quality inspection. This role focuses on edge ML, embedded vision, and hybrid AWS architectures, delivering low-latency, highly reliable solutions in high-throughput production environments. Architect and develop edge-based computer vision systems for automotive inspection and automation
Design, train, and deploy real-time ML/CV models optimized for edge hardware
Optimize inference performance (latency, throughput, memory, power) on industrial edge devices
Build hybrid edge cloud architectures using AWS for model lifecycle management and monitoring
Implement DevOps/MLOps pipelines for edge deployment, updates, and rollback
Integrate vision systems with PLCs, MES, and factory networks
Lead technical decisions and mentor engineers on edge and vision best practices 7+ years of software engineering experience, including edge or embedded systems
Strong proficiency in Python and/or C++ for performance-critical vision workloads
Proven experience with computer vision and ML (OpenCV, PyTorch, TensorFlow, ONNX)
Hands-on experience with edge deployment (Docker, NVIDIA Jetson, Intel, or similar platforms)
Experience with AWS hybrid/edge services and cloud integration
Strong background in CI/CD, DevOps, and production system reliability
Experience delivering systems in automotive or industrial manufacturing environments

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