Edge AI Vision Engineer — On-Device Android Cameras

SGS Consulting; Sacramento (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

SGS Consulting seeks an experienced engineer to design and deploy high-performance computer vision and edge ML pipelines on resource-constrained hardware. You will optimize latency and throughput for multiple edge-AI features and integrate algorithms within the Android camera framework.

You will collaborate with hardware and software teams to bridge sensors with on-device NPUs, profiling memory, power, and timing to ensure real-time performance for biometric verification, image restoration, or

Qualifications

• Proficiency in Python and C/C++ for low-level software development and optimization.
• Familiarity with ML frameworks optimized for edge deployment.
• Solid understanding of computer vision fundamentals and camera architectures.
• Experience with real-time on-device processing and edge AI.
• Knowledge of Android camera framework and multimedia subsystems.

Responsibilities

• Design and deploy high-performance computer vision and ML pipelines on resource-constrained edge hardware.
• Optimize concurrent ML workloads to maximize throughput and minimize latency.
• Integrate edge-AI algorithms within the Android camera framework and multimedia subsystems.
• Collaborate across software and hardware teams to bridge camera sensors with on-device NPUs.
• Profile and optimize memory footprint, power consumption, and execution timing to meet on-device constraints.

Skills

Python

C/C++

Android platform

Edge ML

DSP

Camera architectures

Model optimization

Profiling tools

MAANG experience

Education

Bachelor's degree in CS/EE/CE

Tools

TensorFlow Lite

ONNX Runtime

PyTorch Edge

Job description

SGS Consulting seeks an experienced engineer to design and deploy high-performance computer vision and edge ML pipelines on resource-constrained hardware. You will optimize latency and throughput for multiple edge-AI features and integrate algorithms within the Android camera framework.

You will collaborate with hardware and software teams to bridge sensors with on-device NPUs, profiling memory, power, and timing to ensure real-time performance for biometric verification, image restoration, or