Head of AI/ML Engineering

Fatima Group; Lahore; On-site; PKR 8,000,000 - 16,000,000; Full time

Job summary

Fatima Group is seeking a Head of AI/ML Engineering to lead the development of internal AI platforms and client-facing AI solutions. The role focuses on building scalable AI products for industrial use cases across manufacturing, energy, and logistics, turning data into revenue-generating systems.

You will drive end-to-end ML lifecycle, ensure production-level performance, and mentor a high-performing AI/ML team in a fast-scaling environment.

Qualifications

• 10+ years in AI/ML engineering or applied AI roles.
• Proven experience deploying AI solutions to production at scale.
• Strong expertise in Python, TensorFlow, PyTorch, ML pipelines and MLOps tools (MLflow, Kubeflow).
• Experience with cloud platforms (AWS, Azure, GCP).
• Strong understanding of data engineering fundamentals (Preferred).
• Experience in AI consulting, services, or client delivery roles.
• Exposure to industrial AI / IoT / sensor data use cases.
• Experience with edge AI and real-time inference systems.
• Background in startups or fast-scaling environments.
• Knowledge of AI explainability and model governance.

Responsibilities

• Define and build scalable AI/ML platforms and MLOps infrastructure.
• Establish end-to-end ML lifecycle (data ingestion - training - deployment - monitoring).
• Ensure model scalability, reliability, and performance in production.
• Optimize models for edge environments and low-compute scenarios.
• Implement model monitoring, drift detection, and retraining pipelines.
• Standardize tools, frameworks, and development practice.
• Build and scale AI solution offerings for enterprise clients, including:
• Lead end-to-end delivery: problem definition - modeling - deployment.
• Develop reusable AI frameworks and accelerators.
• Support pre-sales, demos, and client engagements.
• Ensure solutions are practical, explainable, and ROI-driven.

Skills

Python

TensorFlow

PyTorch

MLflow

Kubeflow

Edge AI

Explainability

Model governance

Data engineering

MLOps

Tools

AWS

Azure

GCP

Job description

Role Description

The Head of AI/ML Engineering will lead the development of internal AI platforms, delivery of client-facing AI solutions, and creation of scalable AI products for industrial use cases

.This role sits at the core of the company's value proposition-turning data into production-grade AI systems and revenue-generating solutions across industries such as manufacturing, energy, and logistics.

Responsibilities

Internal AI Platform & MLOps Leadership

• Define and build scalable AI/ML platforms and MLOps infrastructure
• Establish end-to-end ML lifecycle (data ingestion - training - deployment - monitoring)
• Ensure model scalability, reliability, and performance in production
• Optimize models for edge environments and low-compute scenarios
• Implement model monitoring, drift detection, and retraining pipelines
• Standardize tools, frameworks, and development practice

AI Solutions & Client Delivery (External)

• Build and scale AI solution offerings for enterprise clients, including:
• Lead end-to-end delivery: problem definition - modeling - deployment
• Develop reusable AI frameworks and accelerators
• Support pre-sales, demos, and client engagements
• Ensure solutions are practical, explainable, and ROI-driven

AI Product Development & Industrial Innovation

• Define and execute roadmap for AI-powered products
• Collaborate with data and platform teams to build scalable solutions
• Identify opportunities to productize reusable AI components
• Build domain-specific AI solutions tailored for:
• Ensure products are deployable in low-data, low-infrastructure environments

Commercial & Strategic Contribution

• Contribute to revenue generation through AI solutions and products
• Support enterprise sales with technical expertise and solution design
• Help define pricing models and solution packaging
• Build partnerships with AI/cloud ecosystem players

Team Building & Leadership

• Build and lead a high-performing AI/ML engineering team
• Balance research vs applied engineering focus (execution-first mindset)
• Mentor talent and build strong local AI capability
• Foster a culture of rapid experimentation and production delivery

Requirements

• 10 - 15+ years in AI/ML engineering or applied AI roles
• Proven experience in deploying AI solutions to production atscale
• Strong expertise in:
• Python, TensorFlow, PyTorchML pipelines and MLOps tools (MLflow, Kubeflow, etc.)
• Experience with cloud platforms (AWS, Azure,GCP)
• Strong understanding of data engineering fundamentals Preferred
• Experience in AI consulting, services, or client deliveryroles
• Exposure to industrial AI / IoT / sensor data usecases
• Experience with edge AI and real-time inference systems
• Background in startups or fast-scaling environments
• Knowledge of AI explainability and model governance