Remote Edge AI Engineer — Efficient ML on Embedded Devices

Bright Vision Technologies; Naperville (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 platforms, embedded systems, and specialized accelerators. The role emphasizes model compression, quantization, and hardware-aware optimization, with a focus on energy efficiency, memory usage, and on-device security to ship reliable AI capabilities beyond the data center.

The ideal candidate has 8+ years of ML engineering experience and strong Python/C++ skills,

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 that run on resource-constrained edge devices (mobile, embedded, accelerators).
• Address compute, memory, energy, and connectivity trade-offs during deployment.
• Deliver production-grade edge AI capabilities outside the data center with reliable performance.

Skills

Python

C++

Model compression

Quantization

Pruning

Edge inference framework

Mobile/embedded hardware

Production deployment

Performance profiling

On-device privacy

Cross-functional collaboration

Education

Bachelor’s or Master’s in CS/CE

Job description

Bright Vision Technologies is seeking an Edge AI Engineer to design, optimize, and deploy ML models for edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role emphasizes model compression, quantization, and hardware-aware optimization, with a focus on energy efficiency, memory usage, and on-device security to ship reliable AI capabilities beyond the data center.

The ideal candidate has 8+ years of ML engineering experience and strong Python/C++ skills,