AI / ML Engineer

Posted 7 Days Ago
Be an Early Applicant
Riyadh, SAU
In-Office
Mid level
Artificial Intelligence • Information Technology • Software • Analytics
The Role
Design, develop, train, deploy, and monitor ML and generative AI solutions. Build end-to-end ML pipelines, optimize model performance, implement MLOps practices, collaborate with engineers and stakeholders, and deploy/scale models on cloud AI platforms.
Summary Generated by Built In
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)

Skills Required

  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field
  • 3-11 years of professional experience in AI, Machine Learning, or Data Science
  • 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
  • Strong proficiency in Python
  • Experience developing models using TensorFlow or PyTorch
  • Experience with Hugging Face and LangChain
  • Experience with Databricks for data engineering and model development
  • Experience deploying machine learning models into production and implementing MLOps (model versioning, monitoring, CI/CD)
  • Experience working in Agile development environments
  • Excellent communication and collaboration skills
  • Knowledge of Docker, Kubernetes, and CI/CD pipelines
  • Knowledge of prompt engineering, RAG, embeddings, and vector databases
  • Cloud certifications in AWS, Azure, or Google Cloud

Datamatics Technologies Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Datamatics Technologies and has not been reviewed or approved by Datamatics Technologies.

  • Flexible Benefits Feedback suggests flexible timings and work-from-home options are available in some roles. This flexibility is highlighted as part of the employment experience across certain postings and materials.
  • Wellbeing & Lifestyle Benefits Feedback suggests flexibility around time off and remote work supports work-life balance. These elements can help offset leaner cash components for some individuals.

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The Company
Dubai
65 Employees
Year Founded: 2016

What We Do

Datamatics Technologies (DMT) was established in Dubai. We specialize in providing onsite and offshore professional services, covering the full spectrum of Data Analytics and Data Science domains. Our experience of working with diverse industry sectors such as Telecoms, Finance, Government and Manufacturing, across multiple regions enables us to engage and deliver for our clients with confidence. We can offer our full portfolio of services through resource augmentation, managed services, both on T&M or fixed price financial arrangements. Through our end-to-end managed services offering we enable our clients to cut down costs, increase profitability and focus on value addition to their core business activities. Our project and delivery management team are certified in Agile, PMI and ITIL to ensure the planning and execution are carried out using industry best practices. We are working with our clients across Middle East and Africa Region.

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