Machine Learning Engineer - LLMs, RAG & GenAI for Government & Public Sector

Apt Resources; Abu Dhabi; On-site; AED 200,000 - 300,000; Full time

Job summary

A leading recruitment firm is seeking an experienced Machine Learning Engineer in Abu Dhabi to design and deploy AI/ML solutions for government applications. This role involves optimizing AI/ML pipelines, implementing scalable solutions using Python and cloud services like Azure ML, and collaborating with teams to enhance public sector objectives. The ideal candidate will have 6-14 years of hands-on experience in AI/ML and be proficient in LLM architectures and prompt engineering.

Qualifications

• 6-14 years of hands-on experience in AI/ML with a strong focus on LLMs and GenAI.
• Expertise in LLM architectures (Transformers) and prompt engineering.
• Proficiency in Python and ML frameworks like Scikit-learn and LangChain.

Responsibilities

• Develop and optimize AI/ML pipelines for LLMs focused on RAG architectures.
• Implement scalable solutions using Python and cloud-based ML services.
• Deploy and monitor models in production under government compliance standards.

Skills

AI/ML expertise

Experience with LLMs

Proficiency in Python

Knowledge of RAG implementations

Familiarity with cloud platforms

Understanding of government IT standards

Tools

Azure ML

HuggingFace

PyTorch

TensorFlow

LangChain

MLflow

Job description

Overview

Apt Resources is seeking an experienced Machine Learning Engineer for a client in Abu Dhabi's Government & Public Sector. In this role you will design and deploy cutting-edge AI/ML solutions using Large Language Models (LLMs) like GPT, Llama and BERT to drive innovation in public services.

This is an exciting opportunity to work on high-impact projects involving Retrieval-Augmented Generation (RAG) fine-tuning and prompt engineering, ensuring secure, scalable and compliant AI systems for government applications.

Responsibilities

• Develop and optimize AI/ML pipelines for LLMs focusing on RAG architectures, fine-tuning and prompt engineering tailored for public sector needs.
• Implement scalable solutions using Python, LangChain, HuggingFace, PyTorch/TensorFlow and cloud-based ML services (Azure ML preferred).
• Integrate vector and graph databases (Weaviate, Neo4j) into production systems to enhance data retrieval and analysis.
• Deploy and monitor models in production, ensuring adherence to government security and compliance standards.
• Collaborate with cross-functional teams to align AI solutions with public sector objectives (e.g., citizen services, data governance, operational efficiency).

Requirements

• 6-14 years of hands-on experience in AI/ML with a strong focus on LLMs and GenAI.
• Expertise in LLM architectures (Transformers), prompt engineering, and RAG implementations.
• Proficiency in Python and ML frameworks (LangChain, LlamaIndex, HuggingFace, Scikit-learn).
• Experience with cloud platforms (Azure ML, AWS or GCP) and MLOps tools (MLflow, model monitoring).
• Familiarity with vector databases, ETL pipelines, and unstructured data handling.
• Knowledge of government IT standards or secure deployments is a plus.

Benefits

To be discussed