Job Description: AI / ML Engineer

Job Title: AI / ML Engineer
Experience: 3–11 Years
Location: Riyadh (Onsite)
Employment Type: Full-Time

Job Overview

We are seeking a skilled AI / ML Engineer with 3–11 years of experience to design, develop, deploy, and optimize machine learning and generative AI solutions. The ideal candidate will have hands-on expertise in building scalable AI/ML models, working with cloud-native AI platforms, and implementing production-ready machine learning pipelines. Experience with modern AI frameworks, large language models (LLMs), and MLOps practices is highly desirable.

Key Responsibilities

• Design, develop, train, and deploy machine learning and deep learning models for enterprise applications.
• Build and optimize end-to-end ML pipelines for data ingestion, model training, evaluation, and deployment.
• Develop Generative AI and LLM-powered applications using modern AI frameworks.
• Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions.
• Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security.
• Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation.
• Implement MLOps best practices including model versioning, monitoring, and CI/CD automation.
• Stay current with advancements in AI, machine learning, and cloud AI services.

Required Technical Skills

Cloud AI Platforms

• Hands-on experience with GCP Vertex AI or Azure Machine Learning or AWS SageMaker.
• Experience with Azure OpenAI or AWS Bedrock for Generative AI solutions.
• Experience with BigQuery ML and Dataflow for data processing and machine learning workflows.

Programming & Machine Learning

• Strong proficiency in Python.
• Experience developing machine learning solutions using TensorFlow or PyTorch.
• Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts.

Generative AI & LLM Frameworks

• Experience with Hugging Face and LangChain for building LLM-powered applications.
• Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases is preferred.

Data Engineering & Analytics

• Experience with Databricks for data engineering, model development, and analytics workflows.
• Strong understanding of data preprocessing, feature engineering, and large-scale data processing.

MLOps & Deployment

• Experience deploying machine learning models into production.
• Knowledge of Docker, Kubernetes, CI/CD pipelines, and model monitoring is an advantage.

Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 3–11 years of professional experience in AI, Machine Learning, or Data Science.
• Strong analytical, mathematical, and problem-solving skills.
• Experience working in Agile development environments.
• Excellent communication and collaboration skills.

Preferred Skills

• Experience with Large Language Models (LLMs) and Generative AI applications.
• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents.
• Experience with distributed model training and cloud-native AI architectures.
• Cloud certifications in AWS, Azure, or Google Cloud are a plus.

Key Technology Stack

• Cloud AI: GCP Vertex AI or Azure Machine Learning or AWS SageMaker
• Generative AI: Azure OpenAI or AWS Bedrock and Large Language Models (LLMs)
• Data Processing: BigQuery ML and Dataflow and Databricks
• Programming: Python
• Machine Learning Frameworks: TensorFlow or PyTorch
• LLM Frameworks: Hugging Face or LangChain
• MLOps: Docker and Kubernetes and CI/CD (Preferred)

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