Edge AI/Computer Vision Engineer

Reply • Detroit Area, MI

23h

About The Position

Concept Reply, part of the Reply Network, is seeking a Computer Science or Computer Engineering graduate for an engagement deploying AI-driven computer vision for industrial safety. The engineer will work with Concept Reply’s data and AI engineering team and the client’s controls engineers to deliver on-site solutions at manufacturing facilities. The work includes installing and calibrating smart cameras, deploying object detection models on edge hardware, maintaining Linux-based containerized software through GitOps workflows, and connecting detection events to machine signals. The role also involves monitoring field performance and improving datasets and models over time, with increasing autonomy over the engagement. Regular travel to client manufacturing sites is required.

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 determined using market data and job-related qualifications, including prior experience, skills, education, training, and certifications.

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, SSD, or similar.
• 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 or 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 human detection in restricted areas.
• Train, optimize, and deploy object detection models on edge hardware using AXIS ACAP.
• Build and maintain a containerized software stack on Linux, managed through GitOps workflows using 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.

What This Job Offers

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