# 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)