Hybrid Real-Time Autonomous Vision Engineer

Placements24; Randburg; Hybrid; ZAR 600,000 - 1,000,000; Full time

Benefits offered by this job

Competitive salary

Medical aid

Retirement fund

Hybrid work model

Career development

Relocation assistance

Job summary

Placements24 is sourcing a Computer Vision Engineer for our Randburg R&D team. You will design and optimize real-time CV algorithms for autonomous systems, implementing deep learning models for detection, segmentation, pose estimation, and tracking.

You will work with hardware engineers to integrate vision into robotic platforms, using C++ and Python, and you will validate components while staying current with CV/ML research. The role offers a hybrid work model and opportunities for advancement.

Qualifications

• Degree in computer science, electrical engineering, or related field with focus on computer vision or ML.
• 3+ years hands-on CV algorithm development.

Responsibilities

• Design, develop, and optimize CV algorithms for real-time applications.
• Implement deep learning models for object detection, segmentation, pose estimation, and tracking.
• Process large image/video datasets for training and evaluation.
• Collaborate with hardware engineers to integrate vision into robotic platforms.
• Develop robust software using C++ and Python.
• Test and validate CV components rigorously.
• Stay updated with CV/ML advances and contribute to system architecture.

Skills

C++

Python

OpenCV

PCL

CUDA

Teamwork

Agile

Communication

Education

Bachelor's or Master's in CS/EE with CV/ML focus

Tools

ROS

TensorFlow

PyTorch

Keras

Job description

Placements24 is sourcing a Computer Vision Engineer for our Randburg R&D team. You will design and optimize real-time CV algorithms for autonomous systems, implementing deep learning models for detection, segmentation, pose estimation, and tracking.

You will work with hardware engineers to integrate vision into robotic platforms, using C++ and Python, and you will validate components while staying current with CV/ML research. The role offers a hybrid work model and opportunities for advancement.