Remote Intelligent Edge AI Engineer - On-Device Inference

Bright Vision Technologies; Euless, Bedford (TX, TX); On-site; USD 135,000 - 155,000; Full time

Job summary

Bright Vision Technologies is seeking an Intelligent Edge Engineer for a remote, full-time role in the United States. You will design, optimize, and deploy ML models that run efficiently on edge devices such as mobile platforms and embedded systems.

The ideal candidate has 6+ years of ML engineering experience, deep Python and C++ skills, and hands-on use of model compression, quantization, and edge inference frameworks.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field.
• Six or more years of experience in ML engineering, with significant work on edge or mobile AI.
• Strong proficiency in Python and C++.
• Hands-on experience with model compression, quantization, and pruning techniques.
• Experience with at least one major edge inference framework.
• Solid understanding of mobile and embedded hardware architectures.
• Experience deploying ML models to production on mobile or embedded platforms.
• Strong performance engineering and profiling skills.
• Familiarity with on-device privacy and security considerations.
• Strong communication and cross-functional collaboration skills.

Responsibilities

• Design, optimize, and deploy ML models for resource-constrained edge devices.
• Apply model compression, quantization, and hardware-aware optimization.
• Ship AI capabilities in production with attention to resource constraints.

Skills

Python

C++

Edge ML

Model compression

Quantization

Pruning

Edge inference

Mobile hardware

Production deployment

Performance profiling

On-device privacy

Cross-functional collaboration

Education

Bachelor's or Master's degree in CS/CE

Tools

TensorRT

ONNX

PyTorch

Job description

Bright Vision Technologies is seeking an Intelligent Edge Engineer for a remote, full-time role in the United States. You will design, optimize, and deploy ML models that run efficiently on edge devices such as mobile platforms and embedded systems.

The ideal candidate has 6+ years of ML engineering experience, deep Python and C++ skills, and hands-on use of model compression, quantization, and edge inference frameworks.