Remote Edge AI Engineer: On-Device ML for Mobile & Embedded

Bright Vision Technologies; Aurora (IL); Remote; USD 70,000 - 100,000; Full time

Job summary

Bright Vision Technologies is seeking an Edge AI Engineer to design, optimize, and deploy ML models for edge devices, including mobile and embedded platforms. This remote US-based role demands strong skills in model compression, quantization, pruning, and hardware-aware optimization to deliver efficient AI in production.

The ideal candidate has 8+ years in ML engineering, proficiency in Python and C++, and a track record shipping edge AI at scale.

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 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 edge devices.
• Focus on model compression, quantization, and hardware-aware optimization.
• Ship reliable AI capabilities outside the data center.
• Demonstrate production-ready edge AI deployments.

Skills

ML engineering

Python

C++

Model compression

Quantization

Pruning

Edge inference framework

Mobile/embedded hardware

Production deployment

Profiling

On-device privacy

Cross-functional communication

Education

CS/CE degree

Job description

Bright Vision Technologies is seeking an Edge AI Engineer to design, optimize, and deploy ML models for edge devices, including mobile and embedded platforms. This remote US-based role demands strong skills in model compression, quantization, pruning, and hardware-aware optimization to deliver efficient AI in production.

The ideal candidate has 8+ years in ML engineering, proficiency in Python and C++, and a track record shipping edge AI at scale.