Remote Edge AI Engineer — Mobile & Embedded ML

Bright Vision Technologies; Elk Grove (CA); Remote; USD 100,000 - 105,000; Full time

Job summary

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. We are seeking an Edge Computing AI Engineer to design, optimize, and deploy ML models for edge devices, including mobile platforms and embedded systems.

The role requires deep expertise in model compression, quantization, and hardware-aware optimization, plus strong systems engineering to ship AI capabilities outside the data

Qualifications

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.
• Six or more years of experience in ML engineering, with 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.

Skills

Python

C++

Edge AI

Performance profiling

Hardware-aware optimization

Cross-functional communication

Education

Bachelor's/Master's in CS/CE

Tools

TensorFlow Lite

ONNX

Edge inference framework

Model compression tools

Job description

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. We are seeking an Edge Computing AI Engineer to design, optimize, and deploy ML models for edge devices, including mobile platforms and embedded systems.

The role requires deep expertise in model compression, quantization, and hardware-aware optimization, plus strong systems engineering to ship AI capabilities outside the data