Senior AI Engineer: Production ML & Model Quality

Edge; Islamabad; On-site; PKR 1,800,000 - 3,200,000; Full time

Job summary

Edge is seeking a Senior AI Engineer to lead the development and evaluation of machine learning models powering our AI products. You will replace rule-based systems with supervised models, improve model quality, and build production-ready RAG pipelines while driving research for self-hosted AI inference.

This role requires strong experience in applied ML, production AI systems, and end-to-end ML lifecycle ownership, with a focus on delivering scalable AI solutions from data collection to

Qualifications

• 5+ years of experience in Machine Learning or AI engineering.
• Strong proficiency in Python and ML frameworks.
• Hands-on experience with PyTorch, scikit-learn, and Hugging Face.
• Experience building supervised learning models on real-world datasets.
• Strong understanding of data preprocessing, feature engineering, and handling class imbalance.

Responsibilities

• Design, train, and deploy supervised ML models.
• Build and optimize production-grade RAG pipelines.
• Develop evaluation frameworks and benchmarks to measure model performance.
• Own the full ML lifecycle: data collection, labeling, preprocessing, training, and deployment.
• Improve model accuracy via feature engineering, retrieval optimization, and experimentation.
• Work with LLMs to build reliable AI-powered solutions.
• Collaborate with engineering teams to deploy scalable ML solutions to production.
• Continuously evaluate and improve model quality, performance, and inference costs.

Skills

Python

PyTorch

scikit-learn

Hugging Face

ML Engineering

Tools

GitHub Actions

DigitalOcean

Cloudflare

SageMaker

Job description

Edge is seeking a Senior AI Engineer to lead the development and evaluation of machine learning models powering our AI products. You will replace rule-based systems with supervised models, improve model quality, and build production-ready RAG pipelines while driving research for self-hosted AI inference.

This role requires strong experience in applied ML, production AI systems, and end-to-end ML lifecycle ownership, with a focus on delivering scalable AI solutions from data collection to