Edge ML Systems Engineer - Android Camera & On-Device

Us Tech Solutions; Sunnyvale (CA); On-site; USD 96,000 - 138,000; Full time

Job summary

US Tech Solutions in Sunnyvale, CA, seeks a contract engineer to design and deploy high-performance edge computer vision and ML pipelines on resource-constrained hardware.

You will optimize ML workloads for low latency, integrate AI algorithms with Android camera frameworks, and collaborate with software and hardware teams to align sensors with on-device NNUs. This is a 12-month contract.

Qualifications

• Bachelor’s degree in CS/EE/CE or equivalent practical experience.
• Proficiency in Python, C and C++ for low-level software development.
• Experience with edge-optimized ML frameworks (TF Lite, ONNX, PyTorch Edge).
• Familiarity with Android platform stack and camera subsystems.
• Solid CV fundamentals and DSP knowledge.
• Previous AI experience.

Responsibilities

• Design and deploy high-performance computer vision and machine learning pipelines directly onto resource-constrained edge hardware.
• Optimize concurrent ML workloads to maximize throughput and minimize latency when running multiple edge-AI features simultaneously.
• Integrate edge-AI algorithms seamlessly within the Android camera framework and multimedia subsystems.
• Collaborate across software and hardware teams to bridge low-level camera sensor subsystems with on-device neural processing units (NPUs).
• Profile and optimize memory footprint, power consumption, and execution timing to meet strict on-device performance constraints.

Skills

Python

C

C++

ML frameworks

Android

CV fundamentals

DSP basics

AI experience

Education

Bachelor’s degree in CS/EE/CE or equivalent

Tools

TensorFlow Lite

ONNX Runtime

PyTorch Edge

Job description

US Tech Solutions in Sunnyvale, CA, seeks a contract engineer to design and deploy high-performance edge computer vision and ML pipelines on resource-constrained hardware.

You will optimize ML workloads for low latency, integrate AI algorithms with Android camera frameworks, and collaborate with software and hardware teams to align sensors with on-device NNUs. This is a 12-month contract.