Remote Embedded AI Engineer (Edge ML)

Bright Vision Technologies; Issaquah (WA); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an Embedded AI Engineer for 100% remote work in the United States. You will design and deploy edge AI models on resource-constrained devices, optimizing for latency, energy and memory while ensuring on-device privacy and security.

Excellent knowledge of model compression, quantization, and pruning, plus hands-on experience with mobile/embedded platforms and edge inference frameworks, are required.

Qualifications

• Six+ years of ML engineering experience with edge/mobile AI focus.
• Proficient in Python and C++.
• Hands-on with model compression, quantization, and pruning techniques.
• Experience with at least one major edge inference framework.
• Understanding of mobile/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 edge AI solutions for diverse hardware including mobile SoCs, NPUs, and embedded accelerators.
• Apply quantization, pruning, distillation, and architectural optimization to fit models within edge constraints.
• Tune model latency, energy, and memory footprint on target hardware.
• Build cross-platform inference runtimes with TensorFlow Lite, ONNX Runtime, and Core ML.
• Optimize models for accelerator backends including DSPs, NPUs, and mobile GPUs.
• Implement on-device model update, versioning, and rollback workflows for safe staged rollouts.
• Design hybrid edge-cloud architectures that degrade gracefully based on connectivity.
• Build telemetry pipelines that respect privacy while enabling continuous improvement.
• Collaborate with hardware, firmware, and product teams to align AI capabilities with device constraints.
• Implement secure execution paths, model protection, and integrity verification on edge devices.
• Develop benchmarking suites that characterize accuracy, latency, and energy trade-offs across devices.
• Drive responsible AI considerations including on-device privacy and bias evaluation.
• Maintain comprehensive, current technical documentation for onboarding and support.

Skills

Python

C++

Edge AI

Model compression

Quantization

Pruning

Performance profiling

Cross-functional collaboration

Security

Communication

Python ecosystem

Hardware awareness

ML deployment

Education

Bachelor’s or Master’s degree in Computer Science or Computer Engineering

Tools

TensorFlow Lite

ONNX Runtime

Core ML

Job description

Bright Vision Technologies is seeking an Embedded AI Engineer for 100% remote work in the United States. You will design and deploy edge AI models on resource-constrained devices, optimizing for latency, energy and memory while ensuring on-device privacy and security.

Excellent knowledge of model compression, quantization, and pruning, plus hands-on experience with mobile/embedded platforms and edge inference frameworks, are required.