Senior Machine Learning Engineer

Confidential; Dubai; On-site; AED 340,000 - 520,000; Full time

Job summary

Confidential, a leading organization in Dubai, seeks a Senior Machine Learning Engineer to design and deploy production-grade AI solutions for enterprise applications. The role emphasizes scalable ML systems, RAG architectures, semantic search, and secure on-prem deployments.

You will collaborate with cross-functional teams to build intelligent AI capabilities, optimize inference, and automate end-to-end ML pipelines, leveraging PyTorch, LangChain, Hugging Face, Docker, and Kubernetes to deliver

Qualifications

• Minimum 5+ years of Machine Learning Engineering experience, with 7–10 years preferred.
• Experience with Large Language Models (LLMs), Transformers, Hugging Face, LangChain, and Retrieval-Augmented Generation (RAG) architectures.
• Proficiency with Docker, Kubernetes, MLflow, and production ML deployment.
• Experience handling structured and unstructured datasets, including SQL databases and technical documentation.

Responsibilities

• Develop and fine-tune Large Language Models (LLMs) and NLP pipelines for enterprise applications.
• Design and implement Retrieval-Augmented Generation (RAG) architectures and semantic search solutions.
• Build forecasting, supplier risk-scoring, anomaly detection, and optimization models.
• Deploy, optimize, and maintain machine learning models in secure on-premise environments.
• Automate model training, deployment, and inference pipelines using MLOps practices.
• Monitor model performance, reduce inference latency, and continuously improve AI solutions.
• Collaborate with engineering and business teams to deliver production-ready machine learning systems.

Skills

Python programming

Analytical thinking

Cross-functional collaboration

Education

Bachelor's degree in Computer Science/AI/ML/Data Science or related field

Tools

PyTorch

TensorFlow

Scikit-learn

Pandas

NumPy

Docker

Kubernetes

MLflow

Hugging Face

LangChain

Job description

A leading organization is seeking a Senior Machine Learning Engineer to develop advanced AI solutions for enterprise applications. This role is ideal for an experienced professional with expertise in machine learning, large language models (LLMs), and production-grade AI systems capable of solving complex business challenges.

The successful candidate will design, deploy, and optimize scalable machine learning solutions while working closely with cross-functional teams. The role focuses on building intelligent enterprise AI applications, Retrieval-Augmented Generation (RAG) architectures, semantic search capabilities, and secure on-premise deployments.

Key Responsibilities

• Develop and fine-tune Large Language Models (LLMs) and NLP pipelines for enterprise applications.
• Design and implement Retrieval-Augmented Generation (RAG) architectures and semantic search solutions.
• Build forecasting, supplier risk-scoring, anomaly detection, and optimization models.
• Deploy, optimize, and maintain machine learning models in secure on-premise environments.
• Automate model training, deployment, and inference pipelines using MLOps practices.
• Monitor model performance, reduce inference latency, and continuously improve AI solutions.
• Collaborate with engineering and business teams to deliver production-ready machine learning systems.

Requirements

• Minimum 5+ years of Machine Learning Engineering experience, with 7–10 years preferred.
• Strong programming skills in Python.
• Hands-on experience with PyTorch, TensorFlow, Scikit-learn, Pandas, and NumPy.
• Experience working with Large Language Models (LLMs), Transformers, Hugging Face, LangChain, and RAG architectures.
• Proficiency in Docker, Kubernetes, MLflow, and production ML deployment.
• Experience handling structured and unstructured datasets, including SQL databases and technical documentation.
• Strong analytical, problem-solving, and cross-functional collaboration skills.
• Strong knowledge of:
  • Python, PyTorch, TensorFlow, Scikit-learn, Pandas, and NumPy.
  • LLMs, NLP, Hugging Face, LangChain, and Retrieval-Augmented Generation (RAG).
  • Docker, Kubernetes, MLflow, SQL, and enterprise machine learning deployment Bachelor's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field