Edge AI/Computer Vision Engineer

Reply • Detroit, MI

2d • $100,000 - $120,000

About The Position

Concept Reply, part of the Reply Network, supports customers in Automotive, Manufacturing, Smart Infrastructure, and other sectors with IoT and cloud computing solutions. This role involves deploying AI-driven computer vision for industrial safety, working with Concept Reply’s data and AI engineering team and the client’s controls engineers on on-site deliverables. The engineer will install and calibrate smart cameras at manufacturing sites, deploy object-detection models to edge hardware, maintain Linux-based containerized software through GitOps workflows, and collaborate with controls engineers to validate how detection events interact with machinery. The role also includes monitoring field performance, collecting edge cases, and iterating on datasets and models, with increasing autonomy over the engagement. Regular travel to client manufacturing sites is expected.

This is a full-time position with a base compensation range of $100,000–$120,000, plus benefits. Compensation may vary by region and is based on relevant experience, skills, education, training, certifications, and other job-related qualifications.

Requirements

• Bachelor’s degree completed or in the final year in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Strong foundation in programming fundamentals; proficiency in Python and working knowledge of C/C++.
• Solid Linux background, including command line, services, logs, and networking basics.
• Hands-on experience with Docker, including images, Compose, volumes, and container troubleshooting.
• Familiarity and experience with Git-based CI/CD and GitOps practices.
• Coursework or project experience in computer vision or deep learning.
• Willingness to travel regularly to client manufacturing sites.

Nice To Haves

• Experience with computer-vision and deep-learning frameworks such as PyTorch, TensorFlow, or OpenCV, and object-detection models such as YOLO or SSD.
• Experience optimizing models for edge devices using technologies such as TFLite, ONNX, or quantization, on hardware such as AXIS ACAP, NVIDIA Jetson, Coral, or Raspberry Pi.
• Basic understanding of industrial controls, including PLCs, digital I/O, Modbus, or OPC-UA, and machine safety concepts.
• Experience with IP cameras, video streaming (RTSP), or network configuration.
• Prior internship, research, or hands-on hardware/IoT project experience.
• Strong communication skills and comfort working directly with client engineering teams.

Responsibilities

• Install, configure, and calibrate smart cameras at manufacturing sites for detecting people in restricted areas.
• Train, optimize, and deploy object-detection models on edge hardware, including AXIS ACAP.
• Build and maintain a containerized software stack on Linux using GitOps workflows, with Git as the source of truth and automated build, test, and deployment.
• Collaborate with controls engineers to translate detection events into machine signals and validate end-to-end behavior.
• Monitor model performance in the field, collect edge cases, and iterate on datasets and models, taking on increasing autonomy over the engagement.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level