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 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 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)