Senior Machine Learning Engineer (Agentic Systems)

Arbisoft; Lahore; Hybrid; PKR 1,800,000 - 2,400,000; Full time

Job summary

Arbisoft is seeking a Machine Learning Engineer - AI/Agentic Systems to work on a globally recognized travel platform. The role focuses on large-scale data (terabytes) across text and image domains, building labeled datasets, and delivering end-to-end ML solutions from R&D to production.

The ideal candidate will have strong Python and PyTorch skills, experience with agentic AI concepts, and a hands-on approach to deploying ML systems.

Qualifications

• Strong hands-on experience with Python and PyTorch.
• Demonstrated experience owning ML projects end-to-end from problem definition to production deployment.
• Experience 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.

Responsibilities

• Work with very large datasets, terabyte-scale, across text and image domains.
• Build and curate labeled datasets using manual labeling, statistical/ML techniques, and LLM-based approaches.
• Own the full project lifecycle from R&D and experimentation to production deployment.
• Solve open-ended ML/AI problems across text, image, and agentic AI domains.
• Engineer data pipelines to load, process, and parallelize large-scale datasets.

Skills

Python

PyTorch

Agentic AI concepts

Open-ended ML problems

Tools

Docker

Kubernetes

Spark

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.