Staff Machine Learning Engineer

GCS; Abu Dhabi; Hybrid; AED 250,000 - 420,000; Full time

Job summary

GCS in Abu Dhabi is seeking an experienced ML engineer to develop, train and deploy LLM-powered models powering live AI products. You will work with state-of-the-art techniques and build end-to-end applications from model to API, contributing to real-world business solutions.

Ideal candidates have 5+ years in production ML, strong Python, and hands-on experience with LLMs, RAG, and vector databases. The role offers hybrid working in Abu Dhabi and fast onboarding.

Qualifications

• 5+ years of production ML/AI engineering experience.
• Proficiency in Python and deploying LLM-powered apps with REST APIs.
• Hands-on experience with LLMs, RAG, LoRA/QLoRA, and vector databases.

Responsibilities

• Develop, train and deploy ML models for live AI products.
• Build end-to-end LLM-powered applications from model to API.
• Optimize models based on production metrics.
• Define robust data pipelines for high-quality inputs.
• Collaborate with cross-functional teams to solve business challenges.

Skills

Python

LLM deployment

MLOps

REST APIs

PyTorch

TensorFlow

Tools

LangChain

LangGraph

LlamaIndex

Pinecone

Weaviate

pgvector

FastAPI

Flask

Job description

We're partnered with a leading AI company in the UAE building agentic AI products at scale, with access to world-leading models and resources.

This is a hands-on engineering role at the core of their production AI systems. You'll develop, deploy and optimise the ML and LLM-powered models that power live products used across critical sectors. Real production work, not demos or sandboxes.

What you'll do

• Develop, train and deploy ML models and LLM-powered systems that power live AI products


• Work with state-of-the-art techniques, LLMs, RAG, and parameter-efficient fine-tuning, in real business contexts


• Build and ship LLM-powered applications end-to-end, from model to deployed API


• Partner with cross-functional teams to translate business challenges into production AI


• Continuously monitor, evaluate and optimise models against real-world performance


• Implement and manage robust data pipelines for high-quality, reliable input

What we're looking for

• 5+ years in ML or AI engineering with real production experience


• Strong Python, with hands-on experience building and deploying LLM-powered applications (FastAPI/Flask, REST, websockets)


• Proven work with LLMs and parameter-efficient fine-tuning (LoRA, QLoRA), RAG, and agentic systems


• Experience with modern ML frameworks (PyTorch, TensorFlow, scikit-learn) and orchestration libraries (LangChain, LangGraph, LlamaIndex)


• Comfortable with SQL/NoSQL and vector databases (Pinecone, Weaviate, pgvector) for semantic search


• A track record of applying ML to real, business-critical problems

Background we love (not required, but a strong signal):

A competitive-coding background (Kaggle, ACM/ICPC, IOI, TopCoder), a strong technical degree, or experience shipping LLM products at a serious AI company.

How the team works

• Elite environment of ex-FAANG and frontier-lab engineers


• What matters is what you ship, not the hours you spend


• Low ego, high standards. The best idea wins, whoever it comes from


• Minimal bureaucracy, you talk to whoever you need to talk to

The setup

• Abu Dhabi, hybrid working


• Contract-based, Staff level


• Competitive rates


• Moving fast, onboarding in the coming weeks