Edge ML Engineer - Remote, Production-Ready Edge AI

Bright Vision Technologies; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies offers a fantastic opportunity for an Edge ML Engineer to design, optimize, and deploy AI models that run efficiently on edge devices such as mobile platforms and embedded systems.

The role emphasizes model compression, quantization, and hardware-aware optimization, with strong systems engineering to ship AI outside the data center. A senior background with production experience is preferred.

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 efficiently on resource-constrained edge devices, including mobile platforms and embedded systems.
• Address compute, memory, energy, and connectivity trade-offs to ship reliable AI capabilities outside the data center.
• Collaborate with cross-functional teams to productionize edge AI in real-world environments.

Skills

Python

C++

Model compression

Quantization

Pruning

Edge inference framework

Education

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

Job description

Bright Vision Technologies offers a fantastic opportunity for an Edge ML Engineer to design, optimize, and deploy AI models that run efficiently on edge devices such as mobile platforms and embedded systems.

The role emphasizes model compression, quantization, and hardware-aware optimization, with strong systems engineering to ship AI outside the data center. A senior background with production experience is preferred.