Senior Machine Learning Engineer Agentic Systems

Arbisoft

Lahore

Hybrid

PKR 3,000,000 - 6,000,000

Full time

3 days ago
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Job summary

Arbisoft in Lahore is hiring a Machine Learning Engineer – AI/Agentic Systems with 5+ years of experience. This hybrid role requires 3 days per week in the office and base locations in Islamabad or Lahore for large-scale data work on travel AI platforms.

You will work with Python, PyTorch, Docker, and Kubernetes on terabyte-scale text and image datasets, building end-to-end ML solutions and stewarding projects from R&D to production in a globally recognized travel search platform.

Qualifications

  • 5+ years of experience in ML/AI engineering.
  • Experience with large-scale datasets (text and/or image).
  • Hands-on Python and PyTorch with deployment experience.
  • Familiarity with LLMs and agentic AI concepts.
  • Experience using Docker and Kubernetes in production.

Responsibilities

  • Work with terabyte-scale datasets across text and image domains.
  • Build labeled data using manual labeling, statistical/ML techniques, and LLM-based approaches.
  • Own the full project lifecycle from R&D to production deployment.
  • Address open-ended ML/AI problems in agentic contexts.
  • Engineer data pipelines and scalable processing for production systems.

Skills

End-to-end ML projects
Large-scale data handling
Labeled data creation
LLMs and agentic AI concepts
Python
PyTorch
Deployment experience

Tools

Python
PyTorch
Docker
Kubernetes

Job description

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.

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