Computer Vision / AI Engineer

NEDO PAKISTAN provides Software, Hardware and Product Development Solutions Services to the high profile clients ranging from R&D organizations, OEMs, Industrial Organizations, Telecom Operators of Pakistan and Government Institutions for last 25 years with the continued support of our valued suppliers around the country. For further details on our Products, and other information, you may please visit our website www.nedogroup.com and www.nedopakistan.com and www.nedogroup.com. We are having head office at Karachi and branch offices in Lahore and Islamabad.

Currently we are looking for the post of Computer Vision / AI Engineer for our TMS Division (Karachi).

About the Role:

We are looking for a Mid-Level Computer Vision / AI Engineer to help us build a real-time Face Enrollment and Face Verification system using existing CCTV/IP cameras.

The ideal candidate should have hands-on experience with computer vision, face recognition, image/video processing, and Python-based AI development. You will work closely with our existing .NET backend and React frontend team to integrate the AI/CV capabilities into our product.

Key Responsibilities:

• Develop and integrate face detection and face recognition solutions.
• Build face enrollment and verification workflows using CCTV/IP camera streams.
• Work with real-time video streams such as RTSP.
• Implement image and video processing pipelines using Python and OpenCV.
• Work with pre-trained face recognition models and adapt them for our use case.
• Generate and compare face embedding’s for verification.
• Implement face quality checks such as blur, brightness, face size, and pose.
• Implement or integrate liveness / anti-spoofing solutions.
• Optimize face recognition inference for real-time performance.
• Work with CPU/GPU-based inference where required.
• Integrate the AI service with existing .NET APIs.
• Develop APIs/services required for communication between the AI engine and backend.
• Test the system under different lighting, camera angles, distances, and video quality conditions.
• Measure and improve recognition accuracy and system performance.
• Maintain technical documentation and deployment instructions.

Required Skills:

• 2–4 years of relevant experience in Computer Vision / AI / Machine Learning.
• Strong programming skills in Python.
• Hands-on experience with OpenCV.
• Experience with at least one deep learning framework such as:
• PyTorch
• Tensor Flow
• Understanding of:
• Face Detection
• Face Recognition
• Face Embedding’s
• Image Processing
• Video Processing
• Similarity Matching
• Experience working with pre-trained AI/ML models.
• Basic understanding of model inference and performance optimization.
• Experience working with Linux.
• Understanding of REST APIs and integrating AI services with backend systems.
• Ability to troubleshoot and optimize real-time video processing pipelines.Good to Have
• Experience with RTSP/IP cameras.
• Experience with FFmpeg or GStreamer.
• Experience with ONNX Runtime or TensorRT.
• NVIDIA GPU/CUDA experience.
• Experience with face recognition libraries/frameworks.
• Experience with liveness detection / anti-spoofing.
• Experience with Docker.
• Experience deploying computer vision applications in production.

Important:

Candidates should have hands-on project experience in Computer Vision or Face Recognition.

Candidates with only academic/theoretical knowledge of AI/ML but without practical Computer Vision implementation experience may not be suitable for this role.

Collaboration:

You will work with:

• Existing .NET Backend Developers
• Existing React Developers
• Product/Project Team

The primary responsibility of this role will be the Computer Vision / AI component, rather than general frontend or backend development.

Experience:

2–4 years

We are open to candidates with around 2 years of strong hands-on experience if they have built relevant Computer Vision/Face Recognition projects.

Job Location:

SMCH Shahrah-e-Faisal, Karachi, Pakistan

Timings:

Monday – Friday (09:00 AM – 06:00 PM)

Alternate Saturday (09:00 AM – 05:00 PM)

Work Location: In person