Computer Vision AI SDK Engineer

Zebra-Technologies

Greater London

On-site

GBP 70,000 - 100,000

Full time

14 days+

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Benefits offered by this job

Performance-based annual bonus
Learning opportunities

Job summary

Zebra Technologies in London is seeking a Computer Vision Engineer to bridge high-level ML research and production. You will build robust SDKs, automate deployment pipelines, and ensure models run efficiently across edge SoCs to cloud GPUs.

You will optimize model throughput with hardware-specific toolkits and deploy across Qualcomm SoCs, Intel CPUs, and NVIDIA GPUs, collaborating to deliver scalable, high-performance computer vision solutions.

Qualifications

  • Bachelor's or master's degree in Computer Science, Electrical/Electronic Engineering, or related field.
  • Strong proficiency in C++14/17/20 with STL and multi-threading.
  • Experience with model deployment to diverse hardware targets (edge to cloud).
  • Familiarity with Docker and building automated CI/CD pipelines.
  • Bonus: fundamentals of deep learning (CNNs, Transformers, Object Detection).

Responsibilities

  • SDK development to expose computer vision capabilities.
  • Deploy and integrate models across Qualcomm SoCs, Intel CPUs and NVIDIA GPUs.
  • Optimize performance using hardware-specific toolkits.
  • Conduct rigorous evaluation and benchmarking on target hardware.
  • Automate testing and deployment pipelines with Python.

Skills

C++14/17/20
Multithreading
Memory management
STL
Python for automation
Docker familiarity
CNNs/Transformers basics

Education

Bachelor's or Master's in Computer Science or related field

Tools

SNPE/QNN (Qualcomm)
OpenVINO (Intel)
TensorRT (NVIDIA)
TensorFlow Lite

Job description

Zebra Technologies in London is seeking a Computer Vision Engineer to bridge high-level ML research and production. You will build robust SDKs, automate deployment pipelines, and ensure models run efficiently across edge SoCs to cloud GPUs.

You will optimize model throughput with hardware-specific toolkits and deploy across Qualcomm SoCs, Intel CPUs, and NVIDIA GPUs, collaborating to deliver scalable, high-performance computer vision solutions.

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