Senior Edge AI Engineer (Remote)

Bright Vision Technologies; Monroeville (Allegheny County); Remote; USD 100,000 - 155,000; Full time

Job summary

Bright Vision Technologies is seeking an Edge AI Engineer to design, optimize, and deploy ML models on edge devices, including mobile platforms and embedded systems. The role emphasizes compression, quantization, and hardware-aware optimization to run reliably outside data centers.

You will work with cross-functional teams to build cross-platform runtimes, tune performance, and ensure secure, privacy‑preserving edge deployments.

Qualifications

• Bachelor’s or Master’s degree in CS, CE, or a related field.
• 8+ years of ML engineering with edge or mobile AI experience.
• Proficiency in Python and C++ for production ML pipelines.
• Experience deploying ML models to mobile/embedded platforms.
• Familiarity with edge inference frameworks.

Responsibilities

• Design edge AI solutions for mobile SoCs, NPUs, edge accelerators.
• Apply quantization, pruning, distillation to meet edge constraints.
• Tune latency, energy, memory on target hardware.
• Build cross-platform runtimes using TensorFlow Lite, ONNX Runtime, Core ML.
• Optimize for accelerator backends.
• Implement on-device update, versioning, rollback workflows.
• Design hybrid edge-cloud architectures that adapt to connectivity.
• Build privacy-respecting telemetry pipelines.
• Collaborate with hardware, firmware, and product teams.
• Ensure secure execution paths and model protection.
• Develop benchmarking suites for accuracy, latency, energy.
• Drive responsible AI on-device privacy and bias evaluation.
• Maintain architecture documentation and runbooks.
• Stay current with edge AI hardware/software developments.

Skills

Python

C++

Performance engineering

Cross-functional collaboration

Communication

Education

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

Tools

TensorFlow Lite

ONNX Runtime

Core ML

Mobile/Embedded frameworks

Job description

Bright Vision Technologies is seeking an Edge AI Engineer to design, optimize, and deploy ML models on edge devices, including mobile platforms and embedded systems. The role emphasizes compression, quantization, and hardware-aware optimization to run reliably outside data centers.

You will work with cross-functional teams to build cross-platform runtimes, tune performance, and ensure secure, privacy‑preserving edge deployments.