Senior Remote Edge ML Engineer - On-Device AI

United States Digital Space LLC; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an Edge ML Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators.

The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center.

Qualifications

• Six+ years of ML engineering, with edge/mobile AI experience.
• Strong proficiency in Python and C++.
• Hands-on 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/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 and mobile platforms.
• Ensure models meet memory, latency, energy, and connectivity constraints.
• Collaborate with software, hardware, and product teams to ship reliable edge AI capabilities.

Skills

Python

C++

Edge AI

Model compression

Quantization

Mobile/embedded hardware

Production deployment

Profiling

Privacy & security (on-device)

Cross-functional collaboration

Tools

Edge inference framework

Job description

Bright Vision Technologies is seeking an Edge ML Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators.

The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center.