Senior Edge AI Engineer - Remote, Production ML

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

Job summary

Bright Vision Technologies is seeking an Edge AI Engineer for a 100% remote role in the United States. Design, optimize, and deploy ML models for resource-constrained edge devices, including mobile platforms and embedded systems.

The ideal candidate has 8+ years of ML engineering experience, deep knowledge of model compression, quantization, and hardware-aware optimization, and strong software engineering with cross-functional collaboration.

Qualifications

• Bachelor’s or Master’s in CS/CE or related field.
• Six+ years of ML engineering experience with edge/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/embedded hardware architectures.
• Experience deploying ML models to production on mobile/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.
• Profile and optimize performance for mobile/embedded platforms.
• Collaborate with hardware and software teams to ship edge AI.

Skills

Python

C++

Model compression

Quantization

Pruning

Edge inference frameworks

Mobile hardware architectures

Deploy ML on mobile/embedded

Performance engineering

On-device privacy & security

Communication & collaboration

Education

Bachelor’s or Master’s in CS/CE or related

Tools

TensorFlow Lite

PyTorch Mobile

OpenVINO

Job description

Bright Vision Technologies is seeking an Edge AI Engineer for a 100% remote role in the United States. Design, optimize, and deploy ML models for resource-constrained edge devices, including mobile platforms and embedded systems.

The ideal candidate has 8+ years of ML engineering experience, deep knowledge of model compression, quantization, and hardware-aware optimization, and strong software engineering with cross-functional collaboration.