Job Description: Qualification: Bachelor's or Master's degree (16 years of education) in Computer Science, Artificial Intelligence, Machine Learning or a related field from an HEC-recognized university. Preference would be given to foreign qualified candidates with proven track record. Experience: At least 5 years in ML/AI engineering with production deployments; demonstrable LLM application experience (portfolio/GitHub welcome). Skills & Competencies: • Python, PyTorch/TensorFlow, Hugging Face ecosystem • LLM engineering: prompt design, RAG, fine-tuning, vector databases, evaluation • MLOps: MLflow/W&B, Docker/Kubernetes, cloud deployment • Solid software engineering: APIs, testing, Git, CI/CD • NLP for low-resource languages (Urdu/Punjabi) a plus Key Performance Indicators (KPIs): • Number of models and features shipped to production on schedule. • Model accuracy, performance and post-deployment stability metrics. Job Responsibilities: Key Responsibilities / ToRs: • Develop AI applications: LLM apps (RAG, assistants, document intelligence, Urdu/multilingual NLP), classical ML models (prediction, classification, forecasting) as required by pillar use cases. • Build evaluation suites (accuracy, robustness, bias, safety) and run structured experiments before deployment. • Production models: APIs, containers, CI/CD, monitoring, drift detection and re-training workflows. • Integrate AI services with departmental applications alongside Data Engineers and outsourced vendors. • Optimize inference cost and latency across cloud/foundation-model providers. • Document systems and contribute to internal AI standards and reusable components. Last date to apply: 12-Nov-2026