DataQueue is the largest and fastest-growing Voice AI company in the MENA region, deploying AI voice agents across banks, telecoms, and governments — and scaling rapidly.

VoiceHub

, our platform, enables businesses to design, test, and deploy AI voice agents at scale, combining LLMs with a full voice stack including TTS, STT, copilots, speech analytics, and real-time workflows across 25+ languages.

We are looking for a Machine Learning Engineer

with strong expertise in Large Language Models (LLMs), Speech-to-Text (STT), and Text-to-Speech (TTS)

to help us build and optimize the next generation of voice AI systems. In this role, you will work on real-world production problems across model development, inference optimization, deployment, and scale.

You will be part of a team building intelligent conversational systems that must perform reliably under real enterprise requirements, with high standards for latency, accuracy, scalability, and natural interaction quality.

Responsibilities

Requirements

Strong Signal

We would be especially interested in candidates who have already:

• Shipped ML models into production, not just trained them in research settings
• Worked on real-time or low-latency AI systems
• Optimized inference performance for LLM, STT, or TTS workloads
• Built systems that combine multiple AI components in one production pipeline
• Worked with large-scale audio and text datasets in practical environments
• Balanced research thinking with strong engineering execution\
• Experience with multilingual speech or language systems

Nice-to-Have Skills

• Experience with MLOps practices, including CI/CD for ML systems
• Familiarity with model serving and deployment infrastructure
• Understanding of privacy, security, and compliance considerations in AI applications
• Familiarity with conversational AI or voice agent platforms

Why Join DataQueue

• Work with one of the fastest-growing AI companies in the MENA region
• Build systems that solve real problems for enterprises at scale
• Join our vision to become the voice infrastructure of the region
• Work on production systems across LLMs, STT, TTS, and real-time voice workflows
• Be part of a team that moves fast, builds seriously, and operates with high standards

This Role Is Not For You If

• Your experience is mostly academic without strong engineering execution
• You have only experimented with models but not worked on production systems
• You are looking for a role focused only on theory or research without deployment responsibility