Artificial Intelligence Engineer

Punjab Safe Cities Authority (PSCA) is at the forefront of Pakistan’s smart city revolution, enhancing public safety and urban security across Punjab through advanced digital technologies. Operating under the PSCA Act 2016, the Authority manages state-of-the-art Police Integrated Command, Control & Communication Centers (PPIC3) in major cities and is expanding its reach to all districts. PSCA leverages AI-driven systems for traffic monitoring, road safety, and real-time surveillance of critical public spaces, ensuring 24/7 citizen protection and security for high-profile events. The organization also champions citizen-centric initiatives such as virtual police centers and mobile safety applications, making security services more accessible and inclusive. The Artificial Intelligence Engineer will play a vital role in designing, developing, and deploying AI solutions that transform vast amounts of video, image, text, and sensor data into actionable intelligence for mission-critical public safety operations.

Key Responsibilities
- Design, train, and optimize computer vision models for object detection, tracking, segmentation, face and person re-identification, license plate recognition, crowd analysis, and anomaly detection across extensive CCTV networks.
- Implement and fine-tune cutting-edge object detection models including YOLO variants (YOLOv8, YOLO11), RT-DETR, DETR, Grounding DINO, and Segment Anything Model (SAM/SAM 2) for real-time surveillance and traffic management.
- Develop and deploy Vision-Language Model (VLM) solutions such as CLIP, LLaVA, Qwen-VL, and Florence-2 to enable video understanding, natural language video search, scene description, and automated incident summarization.
- Build LLM-powered applications for automated reporting, incident log analysis, emergency call triage, intelligent decision support, and citizen-facing assistants.
- Architect agentic AI workflows and Retrieval-Augmented Generation (RAG) pipelines using LangChain and LangGraph, integrating multiple tools, data sources, and models into reliable multi-step systems.
- Apply Transformer-based architectures across vision, language, and multimodal tasks, utilizing fine-tuning methods like LoRA/QLoRA and prompt engineering.
- Optimize AI models for real-time and edge deployment through quantization, pruning, and inference acceleration frameworks such as TensorRT, ONNX Runtime, OpenVINO, and NVIDIA DeepStream.
- Collaborate with software engineering teams to integrate AI components into existing platforms using APIs and microservices, ensuring scalability, reliability, and low latency.
- Manage the full machine learning lifecycle including data collection, annotation, preprocessing, model training, evaluation, deployment, monitoring, and documentation.
- Work closely with law enforcement and operational staff to translate real-world challenges into effective technical solutions.
- Stay updated with the latest AI research and evaluate emerging models and techniques for potential adoption.

Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related technical discipline.
- Strong foundation in computer science principles including algorithms, data structures, and system design with practical application to AI solutions.
- Proven experience in computer vision tasks such as image and video analysis, object detection, multi-object tracking (e.g., ByteTrack, DeepSORT), and segmentation.
- Hands-on expertise with modern object detection and segmentation models (YOLO family, DETR/RT-DETR, SAM), including training, fine-tuning, and deployment.
- Solid understanding of Transformer architectures and attention mechanisms, including Vision Transformers (ViT).
- Experience with large language models (LLMs) and vision-language models (VLMs), including fine-tuning, prompt engineering, and deployment of open-source models like Llama, Qwen, and Mistral.
- Proficiency with LangChain and LangGraph for building RAG systems, AI agents, and multi-step workflows, along with vector databases such as FAISS, Milvus, Qdrant, or Chroma.
- Strong skills in natural language processing (NLP) for text and speech applications including automated alerts, speech-to-text, and incident log processing.
- Background in pattern recognition and neural networks for anomaly detection and predictive modeling.
- Programming proficiency in Python, with working knowledge of C++ or Java.
- Experience with ML frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, and OpenCV, as well as data tools like pandas, NumPy, and SQL.
- Familiarity with software development best practices including Git, REST APIs, microservices, Docker, and Linux environments.

Preferred Qualifications and Benefits
- Knowledge of real-time systems, distributed architectures, and large-scale data stream processing technologies like Kafka and Redis, particularly in security or urban infrastructure contexts.
- Experience with model serving and MLOps tools such as vLLM, Triton Inference Server, MLflow, and Kubernetes.
- Hands-on experience with edge AI hardware including NVIDIA Jetson and GPU-accelerated video analytics pipelines.
- Contributions to publications, open-source projects, or a portfolio showcasing deployed AI solutions.

Why Join PSCA?
Join PSCA to work on some of Pakistan’s largest real-world AI deployments directly impacting public safety. Benefit from access to extensive, diverse datasets and cutting-edge computing infrastructure. Be part of a mission-driven organization shaping the future of smart cities while advancing your professional growth in an innovative and technology-focused environment.