AI / ML Engineer

Job Overview

Datamatics Technologies is looking for an experienced AI / ML Engineer based in Riyadh to join their full-time onsite team. This position requires 3 to 11 years of experience designing, developing, deploying, and optimizing machine learning and generative AI systems. The role involves working with scalable AI/ML models, cloud-native AI platforms, and creating production-ready ML pipelines. Proficiency in modern AI frameworks, large language models, and MLOps is highly valued.

Key Responsibilities

• Design, develop, train, and deploy machine learning and deep learning models tailored for enterprise use-cases
• Create and enhance end-to-end ML pipelines covering data ingestion, model training, evaluation, and deployment phases
• Develop applications powered by Generative AI and large language models using contemporary AI frameworks
• Collaborate effectively with data engineers, developers, and business teams to deliver AI-driven solutions
• Deploy and maintain ML models on cloud platforms ensuring scalability, reliability, and security
• Fine-tune model performance by leveraging feature engineering, hyperparameter optimization, and ongoing evaluation
• Apply MLOps best practices including model versioning, monitoring, and automation of CI/CD processes
• Keep abreast of the latest trends and advancements in AI, machine learning, and cloud AI services

Technical Skills Required

• Experience with cloud AI platforms such as Google Cloud Vertex AI, Azure Machine Learning, or AWS SageMaker
• Familiarity with Generative AI platforms such as Azure OpenAI or AWS Bedrock for building advanced AI solutions
• Knowledge of BigQuery ML and Dataflow for efficient data processing and ML workflows
• Strong programming skills in Python with expertise in TensorFlow or PyTorch machine learning frameworks
• Solid grasp of machine learning paradigms including supervised, unsupervised, reinforcement, and deep learning
• Experience using LLM frameworks like Hugging Face and LangChain; knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases is beneficial
• Proficient in data engineering tools like Databricks; skilled in data pre-processing and large-scale data handling
• Experience deploying ML models in production with familiarity in Docker, Kubernetes, CI/CD pipelines, and model monitoring considered advantageous

Qualifications and Experience

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related fields
• 3 to 11 years of professional experience specifically in AI, machine learning, or data science roles
• Strong analytical thinking, mathematical aptitude, and problem-solving abilities
• Experience working within Agile development methodologies
• Excellent communication and teamwork skills

Preferred Skills

• Hands-on experience with large language models (LLMs) and generative AI applications
• Understanding of Retrieval-Augmented Generation, vector databases, and building AI agents
• Experience with distributed training of models and cloud-native AI system architectures
• Possession of cloud platform certifications (AWS, Azure, Google Cloud) is an asset

Technology Stack

• Cloud AI Platforms: GCP Vertex AI, Azure Machine Learning, AWS SageMaker
• Generative AI Solutions: Azure OpenAI, AWS Bedrock, Large Language Models
• Data Processing Tools: BigQuery ML, Dataflow, Databricks
• Programming Languages: Python
• ML Frameworks: TensorFlow, PyTorch
• LLM Frameworks: Hugging Face, LangChain
• MLOps Tools: Docker, Kubernetes, CI/CD Pipelines