Machine Learning Engineer

Involved Solutions LTD.; Dubai; On-site; AED 180,000 - 300,000; Full time

Job summary

Involved Solutions LTD. is hiring a Machine Learning Engineer to join a fast-scaling UAE tech business. You will work on pushing production-grade ML systems, fine-tuning foundation models and building agentic workflows that operate at scale on GPU infrastructure.

You will collaborate with product and engineering teams to turn business challenges into live ML deployments, focusing on efficiency, cost, and measurable impact for customers in the region.

Qualifications

• 5+ years hands-on ML engineering experience with production deployments.
• Strong Python and PyTorch experience; familiarity with Hugging Face Transformers.
• Hands-on with LLMs in production, including fine-tuning and evaluation.
• Solid grounding in MLOps and cloud ML platforms (AWS/Azure/GCP).
• Experience with model serving and inference optimisation is a plus.

Responsibilities

• Fine-tune and adapt foundation models using LoRA, QLoRA, DPO and RLHF, including multilingual and Arabic use cases.
• Build production agentic systems with tool use, multi-step reasoning, retrieval and orchestration.
• Optimise inference for latency and cost using quantisation, distillation and serving frameworks like vLLM and TensorRT-LLM.
• Design evaluation frameworks to measure model quality, safety and drift in live environments.
• Develop the MLOps backbone covering training pipelines, experiment tracking and CI/CD for ML on GPU infrastructure.
• Collaborate with product and engineering teams to translate business problems into scalable ML solutions.

Skills

Python

PyTorch

LLMs in production

MLOps

Cloud platforms

Model serving

Tools

vLLM

TensorRT-LLM

LoRA

QLoRA

DPO

RLHF

Job description

We have partnered with a fast-scaling technology business in the UAE to hire a Machine Learning Engineer. This is a team working on the hard end of applied AI: fine-tuning foundation models, building agentic systems that take real actions, and pushing inference to run faster and cheaper on serious GPU infrastructure. The models you build will be live in production, used by real customers and measured on commercial outcomes.

This role suits an engineer who wants to work with the current generation of ML tooling, not maintain a legacy pipeline. You will have the compute, the data and the autonomy to do it properly.

About the role:

• Fine-tune and adapt open-source and proprietary foundation models using techniques such as LoRA, QLoRA, DPO and RLHF, including multilingual and Arabic language use cases
• Build and ship production agentic systems with tool use, multi-step reasoning, retrieval and orchestration
• Optimise inference for latency and cost using quantisation, distillation and serving frameworks such as vLLM and TensorRT-LLM
• Design evaluation frameworks that measure model quality, safety and drift in live environments
• Build the MLOps backbone covering training pipelines, experiment tracking, model registries, CI/CD for ML and monitoring on GPU infrastructure
• Work with product and engineering teams to turn business problems into ML systems that ship and move the numbers

About you:

• 5 years of hands-on experience in machine learning engineering, with a track record of deploying models into production
• Strong Python and deep experience with PyTorch, plus Hugging Face Transformers or equivalent
• Practical experience with LLMs in production, including fine-tuning, RAG and evaluation
• Solid grounding in MLOps and cloud ML platforms on AWS, Azure or GCP
• Experience with model serving and inference optimisation, or a clear appetite to go deep on it
• Exposure to multimodal models, distributed training or GPU cluster work is a strong advantage
• Based in the UAE or willing to relocate