Senior Data Scientist – Generative AI, Machine Learning & MLOps | Dhahran, Saudi Arabia

Location

Dhahran, Saudi Arabia

Job Category

• Information Technology (IT) & Software
• Science & Research
• Engineering & Technical

Job Overview

We are seeking an experienced Data Scientist to join our team in Dhahran, Saudi Arabia, on a full-time basis. The position is suited to professionals with 6–14 years of experience in Data Science, Machine Learning, or related disciplines who can develop, productionize, and scale advanced Artificial Intelligence and Machine Learning solutions.

The successful candidate will work across Generative AI, Large Language Models, Retrieval-Augmented Generation, vector databases, Agentic AI, time-series forecasting, and anomaly detection. The role will also involve productionizing machine learning models using Python, FastAPI, MLflow, Docker, and Kubernetes, while collaborating on cloud infrastructure and MLOps practices.

This opportunity offers strong career growth potential within advanced AI and machine learning engineering. Professionals will gain exposure to emerging Agentic AI architectures, enterprise GenAI applications, cloud-based ML deployment, MLOps, model optimization, and production AI systems. Relevant professional certifications and advanced training in cloud, AI, machine learning, and MLOps can further support long-term career progression.

Key Responsibilities

• Design and deploy Generative AI solutions using Large Language Models (LLMs).
• Develop Retrieval-Augmented Generation (RAG) applications.
• Implement vector database solutions for AI and machine learning applications.
• Build multi-agent AI applications using LangGraph, LangChain, CrewAI, and AutoGen.
• Design and develop Agentic AI workflows for enterprise applications.
• Develop Time-Series Forecasting models for advanced analytical use cases.
• Build Anomaly Detection models to identify patterns and operational deviations.
• Productionize machine learning models using Python and FastAPI.
• Implement ML model lifecycle management using MLflow.
• Containerize machine learning applications using Docker.
• Deploy and manage ML solutions using Kubernetes.
• Collaborate on cloud infrastructure for AI/ML deployment and scaling.
• Optimize model performance, scalability, and production reliability.
• Implement and maintain MLOps practices across the machine learning lifecycle.
• Support CI/CD pipelines for AI and ML workflows.
• Collaborate with technical and business stakeholders to develop practical AI solutions.
• Monitor and continuously improve production machine learning systems.

Requirements & Qualifications

• 6–14 years of professional experience in Data Science, Machine Learning, or a related field.
• Strong programming skills in Python.
• Hands-on experience with FastAPI.
• Experience with Generative AI technologies and Large Language Models.
• Strong understanding of prompt engineering.
• Experience with Retrieval-Augmented Generation (RAG) and embeddings.
• Familiarity with Agentic AI frameworks and multi-agent workflows.
• Experience with LangGraph, LangChain, CrewAI, and/or AutoGen is advantageous.
• Experience with Docker and Kubernetes.
• Hands-on experience with CI/CD pipelines.
• Knowledge of cloud platforms and cloud-based AI/ML deployment.
• Strong understanding of MLOps practices.
• Experience developing or deploying machine learning models in production environments.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration capabilities.

Salary, Benefits & Career Growth

The job posting does not specify a salary, compensation package, or benefits.

This full-time opportunity provides exposure to advanced Generative AI, Agentic AI, machine learning, MLOps, cloud infrastructure, forecasting, anomaly detection, and production AI systems. The role offers significant professional development opportunities for candidates interested in building scalable enterprise AI solutions.

Career progression may include opportunities toward Senior Data Scientist, Lead Data Scientist, Machine Learning Engineer, AI Engineer, MLOps Engineer, AI Architect, and AI/ML leadership positions. Advanced training and certifications in cloud platforms, machine learning, Generative AI, Kubernetes, and MLOps can further support long-term career growth.

Application Process

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Employment Details

Employment Type: Full-time
Experience: 6–14 years
Location: Dhahran, Saudi Arabia