Senior Machine Learning Engineer - AI/Agentic System

Brickstech; Lahore; Hybrid; PKR 2,400,000 - 4,800,000; Full time

Job summary

Arbisoft in Pakistan is hiring a Machine Learning Engineer – AI/Agentic Systems to support a globally recognized travel platform. The role is hybrid with three days in the office and bases in Islamabad or Lahore. You will work on terabyte-scale datasets across text and image domains, building scalable ML solutions from data to deployment.

You should have strong Python and PyTorch skills, experience with LLMs and agentic AI concepts, and production exposure with Docker/Kubernetes.

Qualifications

• Five+ years of experience in ML/AI roles.
• End-to-end ownership of ML projects from problem to deployment.
• Experience with large-scale text/image data pipelines.
• Experience building labeled datasets from limited ground truth.
• Familiarity with LLMs and agentic AI concepts; production exposure is a plus.

Responsibilities

• Work with terabyte-scale datasets across text and image domains.
• Build labeled datasets using labeling, statistics, ML techniques, or LLM-based approaches.
• Own the full ML project lifecycle from R&D to production deployment.
• Solve open-ended ML/AI problems and design scalable data pipelines.
• Collaborate across teams to deploy solutions in production.

Skills

Python

PyTorch

Agentic AI

LLMs

Docker

Kubernetes

Tools

Docker

Kubernetes

Job description

Experience: 5 years +Work Mode: Hybrid, 3 days/week from office (mandatory)
Base Location: Islamabad, Lahore
Data Scale: Terabyte-scale datasets, across text and image domains
Core Domains: Text, Image, and Agentic AI
Core Stack: Python, PyTorch, Agentic AI/LLMs, Docker, Kubernetes
Arbisoft is hiring a Machine Learning Engineer – AI/Agentic Systems for one of our client projects.
Our client is a globally recognized travel search platform, used by millions of travelers worldwide to search, compare, and book flights, hotels, and rental cars. The client is investing heavily in AI-powered and agentic travel planning experiences, alongside its core large-scale search and personalization systems.
What You'll Be Doing

• Working with Large-Scale Data: We work with very large datasets, often at terabyte scale, across both text and image domains.
  
• Building Labeled Data: Many of our problems text, image, and agentic AI start with little or no labeled data. You'll get time and ownership to build/curate labeled datasets using manual labeling, statistical/ML techniques, and LLM-based approaches.
  
• Owning the Full Project Lifecycle: Every team member is responsible for the complete project lifecycle, from R&D and experimentation to production deployment.
  
• Solving Open-Ended Problems: We work on image, text, and agentic AI problems, so experience solving open-ended ML/AI problems is important.
  
• Engineering Data at Scale: You should be comfortable handling, loading, processing, and parallelizing large-scale datasets efficiently.
  

What We’re Looking For

• Strong hands-on experience with Python and PyTorch
  
• Demonstrated experience owning ML projects end-to-end from problem definition to production deployment
  
• Experience working with large-scale datasets (text and/or image) with strong data engineering fundamentals
  
• Exposure to building labeled datasets from limited/no ground truth via manual labeling, statistical/ML techniques, or LLM-based approaches
  
• Familiarity with LLMs and agentic AI concepts production experience is a strong plus, but hands-on experimentation, side projects, or research exposure will also be considered
  
• Working knowledge of Docker and Kubernetes for deployment
  
• Ability to independently explore a problem, experiment with different approaches, build the required data pipeline, and take the solution to production
  

Nice to Have

• Experience with distributed data processing tools (Spark, Ray, Dask)
  
• Open-source contributions or public technical writing related to ML/LLMs
  
• Prior experience in a product company or applied AI/data-focused software house serving global clients
  

What We Value: Someone who can independently explore a problem, experiment with different approaches, build the required data pipeline, and ultimately take the solution to production.