AI / ML Engineer

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

Job Description

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)