AI / ML Engineer

Job Description: AI / ML Engineer
Job Title: AI / ML Engineer
Experience: 3–11 Years
Location: Riyadh (Onsite)
Employment Type: Full-TimeJob 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 servicesRequired Technical SkillsCloud 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 workflowsProgramming & 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 conceptsGenerative 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 preferredData Engineering & Analytics

– Experience with Databricks for data engineering, model development, and analytics workflows
– Strong understanding of data preprocessing, feature engineering, and large-scale data processingMLOps & Deployment

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

– 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 skillsPreferred 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 plusKey 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)