Head of AI/ML Engineering

hrsi; Lahore; On-site; PKR 3,500,000 - 8,000,000; Full time

Job summary

HRSI in Lahore seeks an experienced AI/ML leader to build scalable internal platforms and MLOps infrastructure for production-grade AI systems. You will drive edge deployments and real-time inference for industrial use cases, including manufacturing, energy, and logistics.

The role also involves leading enterprise client delivery, developing reusable AI frameworks, and collaborating with cloud teams to ensure robust, explainable solutions with measurable ROI.

Qualifications

• Extensive experience in AI/ML engineering or applied AI roles.
• Proven track record deploying AI solutions to production at scale.
• Strong expertise in Python and ML frameworks (TensorFlow, PyTorch).
• Experience with MLOps tools and cloud platforms (AWS/Azure/GCP).

Responsibilities

• Lead internal AI platform development and MLOps infrastructure.
• Ensure production model scalability, reliability, and performance.
• Drive AI solutions for enterprise clients andROI-driven outcomes.
• Develop scalable AI products for industry use cases (manufacturing, energy, logistics).
• Mentor AI/ML teams and foster rapid experimentation.

Skills

Python

TensorFlow

PyTorch

ML pipelines

MLOps

MLflow

Kubeflow

AWS

Azure

GCP

Data engineering

Explainability

Edge AI

Job description

Company Overview: HRSI is leading the executive search on behalf of one of Pakistan's leading conglomerates for their Technology Division. As a forward‑thinking partner, the organization is dedicated to delivering smart, scalable, and secure AI service offerings and consultancy.

Position Title: Functional Oracle HCM Consultant

Employment Type: Permanent (On-Site)

Location: Lahore

Role Description: The Head of AI/ML Engineering will lead the development of internal AI platforms, deliveryof 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 productiongrade AI systems and revenue‑generating solutions across industries such asmanufacturing, energy, and logistics.

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

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