Computer Vision Engineer - Object Detection & Recognition

Placements24; Stellenbosch; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary

Medical and retirement benefits

Generous annual leave

Hybrid work model

Job summary

Placements24 is seeking a Computer Vision Engineer in Stellenbosch to design, develop, and deploy CV models for object detection, recognition, and image analysis. The role blends in-office collaboration with remote flexibility in a hybrid setup.

You will work with a team of engineers and researchers, applying deep learning and software development skills to real-time and embedded applications, contributing to AI-powered products and services.

Qualifications

• Bachelor's or Master's in CS/EE with focus on CV or ML
• Proven experience in developing computer vision applications
• Strong Python and C++ programming skills
• Proficiency with TensorFlow or PyTorch
• Experience with OpenCV and image processing techniques

Responsibilities

• Develop CV algorithms for detection, recognition, segmentation, and tracking
• Train and deploy neural networks for visual tasks using TensorFlow/PyTorch
• Process large image/video datasets and optimize real-time performance
• Collaborate with engineers to deploy CV models in production environments
• Research state-of-the-art CV techniques and contribute to system design

Skills

Python

C++

OpenCV

TensorFlow

PyTorch

Education

Bachelor's degree in Computer Science or Electrical Engineering

Master's degree preferred

Tools

TensorFlow

PyTorch

OpenCV

Job description

About the Role

Our client is seeking a highly skilled Computer Vision Engineer to contribute to their innovative work in the AI & Emerging Technologies space. This role is based in Stellenbosch, Western Cape , and offers a flexible Hybrid work arrangement, allowing for a balance between in-office collaboration and remote flexibility. You will be responsible for designing, developing, and deploying cutting-edge computer vision models, focusing on object detection, recognition, and image analysis. This is a fantastic opportunity to work on challenging projects that push the boundaries of visual AI and contribute to groundbreaking applications. You will collaborate with a team of talented engineers and researchers, bringing your expertise in algorithms, deep learning, and software development to life. Your work will directly impact the functionality and capabilities of our AI-powered products and services.

Key Responsibilities

• Develop and implement advanced computer vision algorithms and models for object detection, recognition, segmentation, and tracking.
• Utilize deep learning frameworks (e.g., TensorFlow, PyTorch) to build and train neural networks for visual tasks.
• Process and analyze large image and video datasets.
• Optimize model performance for real-time applications and embedded systems.
• Collaborate with software engineers to integrate computer vision models into production environments.
• Conduct research on state-of-the-art computer vision techniques and explore their application.
• Write clean, efficient, and well-documented code.
• Troubleshoot and debug computer vision systems.

Requirements

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field with a focus on computer vision or machine learning.
• Proven experience in developing computer vision applications.
• Strong programming skills in Python and C++.
• Proficiency with deep learning frameworks like TensorFlow or PyTorch.
• Experience with computer vision libraries such as OpenCV.
• Solid understanding of image processing techniques and algorithms.
• Familiarity with 3D vision, SLAM, or augmented reality is a plus.
• Ability to work effectively in a team and communicate technical concepts clearly.
• Experience with cloud platforms and distributed computing is beneficial.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive medical and retirement benefits.
• Generous annual leave.
• Opportunities for professional growth and learning.
• Access to cutting-edge technology and research facilities.
• Hybrid work model supporting work-life integration.
• Dynamic and innovative team environment.