C++ Computer Vision AI Engineer, Medior

Here Technologies
Charing Cross, United Kingdom
10 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Remote
Charing Cross, United Kingdom

Tech stack

Artificial Intelligence
Computer Vision
C++
Memory Management
Python
Machine Learning
Object Detection
Performance Tuning
TensorFlow
Software Engineering
Data Processing
Multithreading
Graphics Processing Unit (GPU)
Standard Template Library (STL)
Deep Learning
Docker

Job description

  • SDK Development (C++) Design, develop, and maintain high-performance software development kits (SDKs) to expose computer vision capabilities to end-users and internal products.

  • Model Deployment and Integration Port, convert, and deploy machine learning models across various hardware targets, including Qualcomm SoCs, Intel CPUs, and NVIDIA GPUs.

  • Performance Optimization Use hardware-specific toolkits to optimize model throughput without sacrificing accuracy.

  • Evaluation & Benchmarking Conduct rigorous testing and evaluation of models on target hardware to ensure performance metrics meet expectations.

  • Automation Build and maintain automation scripts and CI/CD pipelines using Python to streamline the model testing and deployment life cycle.

Requirements

We are seeking a skilled and motivated Computer Vision Engineer to join our team. In this role, you will bridge the gap between high-level machine learning research and high-performance production environments. You will be responsible for building robust SDKs, automating deployment pipelines, and ensuring our models run efficiently across a diverse hardware landscape, from edge SoCs to powerful cloud GPUs., * Deep understanding of C++14/17/20, including STL, memory management, and multi-threading.

  • Strong ability to write clean, maintainable Python for automation, and data processing.
  • Hands-on experience with at least one of the following frameworks:
  • SNPE/QNN (Qualcomm)
  • OpenVino (Intel)
  • TensorRT (Nvidia)
  • TensorFlow Lite
  • Familiarity with Docker for creating consistent development and deployment environments.

Bonus:

  • Understanding Deep Learning fundamentals (CNNs, Transformers, Object Detection).
  • Experience with model conversion and quantization (i.e. PTQ, QAT).

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