Principal AI/ML Engineer

NextGENi - A DotZero Company; Karachi Division; Hybrid; PKR 3,500,000 - 7,000,000; Full time

Benefits offered by this job

ITS exposure

Job summary

NextGENi is seeking a Principal AI/ML Engineer to join our senior AI team in Karachi on a hybrid basis. You will lead for pedestrian and vehicle detection, tracking and counting, and drive YOLO-based model improvements for high-traffic, real-world environments.

You will optimize end-to-end video analytics pipelines, work with large video datasets, and ensure scalable, reliable deployments in mission-critical contexts. Proven production experience in computer vision is highly valued.

Qualifications

• 8+ years of engineering experience with 4+ years of hands-on computer vision experience.
• Principal or Lead-level ability to independently diagnose and solve complex AI/model-performance problems.
• Deep practical experience with YOLO and modern object detection architectures.
• Strong experience with object detection, multi-object tracking, pedestrian/vehicle counting and video analytics.
• Proven experience improving the accuracy of computer vision models deployed in real-world production environments.

Responsibilities

• Lead the optimization of computer vision models for pedestrian and vehicle detection, tracking, classification and counting.
• Diagnose sources of model inaccuracy and implement improvements to achieve and maintain 90%+ accuracy.
• Develop, train, fine-tune, benchmark, and optimize YOLO-based object detection models and related computer vision architectures.
• Improve model performance under challenging real-world conditions, including extreme crowd density, occlusion, variable lighting, camera angles and high traffic volumes.
• Work with large volumes of video captured from deployed camera units and improve the end-to-end inference and counting pipeline.
• Evaluate model performance, establish appropriate accuracy metrics, and systematically identify false positives, false negatives, tracking errors and counting discrepancies.
• Provide principal-level technical guidance and collaborate closely with an existing team of Senior AI Engineers.
• Ensure models are scalable, reliable and suitable for deployment across mission-critical, large-scale environments.

Skills

Python

PyTorch

OpenCV

YOLO

Computer Vision

Object Detection

Multi-Object Tracking

Pedestrian Counting

Vehicle Counting

Video Analytics

Tools

YOLO-based Models

PyTorch

OpenCV

Job description

About NextGENi

NextGENi (Next Generation Innovations) is transforming how regional startups build their technology teams. We help ambitious founders build and manage their offshore technology teams at twice the speed and fraction of the cost. We have built tech teams for some of the leading startups in the region including Careem, Dubizzle, and Kavak. Our mission is to create exceptional tech teams while maintaining an unparalleled culture and the highest regard for professional principles.

Job Details

• Role: Principal AI/ML Engineer
• Location: Karachi (Hybrid)
• Type: Full-Time
• Experience Range: 8+ years

About NextGENi

NextGENi (Next Generation Innovations) is transforming how regional startups build their technology teams. We help ambitious founders build and manage their offshore technology teams at twice the speed and fraction of the cost. We have built tech teams for some of the leading startups in the region including Careem, Dubizzle, and Kavak. Our mission is to create exceptional tech teams while maintaining an unparalleled culture and the highest regard for professional principles.

About The Role

We are seeking an experienced Principal AI/ML Engineer to join an existing senior AI team working on complex, large-scale computer vision systems. In this role, you will provide deep technical expertise in pedestrian and vehicle detection, tracking, and counting, with a strong focus on improving model accuracy and reliability in dense, real-world environments. Working alongside a team of Senior AI Engineers, you will optimize and fine-tune YOLO-based models and end-to-end video analytics pipelines to achieve 90%+ counting accuracy. This is a highly practical, hands-on role where proven experience solving complex computer vision challenges in production is valued significantly more than certifications or formal credentials.

Responsibilities

• Lead the optimization of computer vision models for pedestrian and vehicle detection, tracking, classification and counting.
• Diagnose sources of model inaccuracy and implement improvements to achieve and maintain 90%+ accuracy.
• Develop, train, fine-tune, benchmark, and optimize YOLO-based object detection models and related computer vision architectures.
• Improve model performance under challenging real-world conditions, including extreme crowd density, occlusion, variable lighting, camera angles and high traffic volumes.
• Work with large volumes of video captured from deployed camera units and improve the end-to-end inference and counting pipeline.
• Evaluate model performance, establish appropriate accuracy metrics, and systematically identify false positives, false negatives, tracking errors and counting discrepancies.
• Provide principal-level technical guidance and collaborate closely with an existing team of Senior AI Engineers.
• Ensure models are scalable, reliable and suitable for deployment across mission-critical, large-scale environments.

Key Requirements

• 8+ years of engineering experience with 4+ years of hands-on computer vision experience.
• Principal or Lead-level ability to independently diagnose and solve complex AI/model-performance problems.
• Deep practical experience with YOLO and modern object detection architectures.
• Strong experience with object detection, multi-object tracking, pedestrian/vehicle counting and video analytics.
• Proven experience improving the accuracy of computer vision models deployed in real-world production environments.
• Experience handling challenges such as dense crowds, overlapping objects/occlusion, object re-identification, camera perspective and variable environmental conditions.
• Strong Python and modern AI/ML framework experience, ideally including PyTorch and OpenCV.
• Experience evaluating models using appropriate detection/tracking metrics and translating model improvements into measurable production accuracy.
• Ability to work effectively within an existing senior engineering team while providing principal-level technical leadership.
• Production experience and demonstrated technical capability are prioritized over certifications.

Nice To Have

• Previous experience with intelligent transportation systems (ITS), traffic analytics, smart cities, crowd analytics, surveillance/video analytics or similarly large-scale computer vision deployments.