Senior AI Engineer, 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

• Location: Onsite at our Islamabad office.
• Hiring Market: We are currently hiring Islamabad based candidates only.
• Working Hours: 7:00 PM to 4:00 AM (PKT).
• Please apply only if you are comfortable with the above requirements.

About the Role

We are looking for a Senior AI Engineer to lead the development and evaluation of machine learning models that power our AI products. You will replace rule based systems with supervised learning models, improve model quality, build production ready RAG pipelines, and drive research for self hosted AI inference.

This role is ideal for someone with strong experience in applied machine learning, production AI systems, and end to end ownership of the ML lifecycle.

Key Responsibilities

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

Requirements

• 5+ years of experience in Machine Learning or AI Engineering.
• Strong proficiency in Python.
• Hands on experience with PyTorch, scikit learn, and Hugging Face.
• Experience building supervised learning models using real world datasets.
• Strong understanding of data preprocessing, feature engineering, and handling class imbalance.
• Experience building and optimizing production RAG systems.
• Experience designing evaluation frameworks and model benchmarking.
• Ability to independently collect, label, clean, and prepare training datasets.
• Strong analytical and problem solving skills.

Nice to Have

• RLHF (Reinforcement Learning from Human Feedback)
• Amazon SageMaker
• Experience in fintech, insurtech, legal tech, or other regulated industries
• Inference cost optimization

Languages & Frameworks: Python, PyTorch, scikit learn, Hugging Face

AI & ML: Large Language Models, RAG, Supervised Learning, Model Evaluation

Infrastructure: DigitalOcean, Cloudflare, GitHub Actions

If you're passionate about building production grade AI systems, improving model quality, and solving real world machine learning challenges, we'd love to hear from you.