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# Computer Vision/ Machine Learning Engineer

- **Company:** Experis
- **Location:** Sunnyvale, CA, United States
- **Contract:** Permanent contract
- **Skills:** Computer Vision, Tensorflow
- **Published:** September 26, 2026
- **Apply:** https://www.experis.com/en/job/412806/embedded-software-engineer-ii

## About the Role

Our client, a leading innovator in the technology industry, is seeking a Computer Vision/ Machine Learning Engineer to join their dynamic team. You will be an integral part of the Engineering Department supporting the development of cutting-edge computer vision and machine learning solutions. The ideal candidate will demonstrate strong problem-solving skills, adaptability, and a collaborative spirit, which will align successfully within the organization., + Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.

 + Proficiency in Python, C, and C++ for low-level software development and optimization.
 + Experience with machine learning frameworks optimized for edge deployment, such as TensorFlow Lite, ONNX Runtime, or PyTorch Edge.
 + Familiarity with the Android platform stack, specifically regarding multimedia or camera subsystem integration.
 + Solid understanding of computer vision fundamentals, digital signal processing (DSP), or basic camera architectures.

## Description

+ 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.
What's Needed?