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AI & Machine Learning Consultant

Job in Riyadh, Riyadh Region, Saudi Arabia
Listing for: Accenture
Full Time position
Listed on 2026-08-21
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Engineering, Data Scientist
Salary/Wage Range or Industry Benchmark: 240000 - 360000 SAR Yearly SAR 240000.00 360000.00 YEAR
Job Description & How to Apply Below

Role Overview

As an AI & Machine Learning Consultant
, you will design, develop, and implement Artificial Intelligence (AI) and Machine Learning (ML) solutions that help organizations solve business challenges through advanced analytics, automation, and Generative AI technologies. You will leverage cloud-based AI services, modern engineering practices, and scalable data platforms to deliver innovative, production-ready solutions while supporting the full AI lifecycle from data preparation through model deployment and optimization.

Key Responsibilities
  • Design and develop Artificial Intelligence (AI) and Machine Learning (ML) solutions using cloud-native AI platforms and services.
  • Build and maintain scalable data pipelines to support data ingestion, feature engineering, model training, deployment, and production operations.
  • Implement Dev Ops and MLOps practices to automate model development, deployment, monitoring, and lifecycle management.
  • Develop, customize, and deploy Deep Learning, Generative AI, and Large Language Model (LLM) solutions to address business and technical requirements.
  • Assess business needs, data availability, and infrastructure constraints to recommend and implement AI solutions that deliver measurable outcomes.
  • Support AI workloads across cloud environments, edge computing platforms, and High-Performance Computing (HPC) infrastructures.
  • Conduct research and experimentation on emerging AI technologies, algorithms, models, and simulation techniques to solve complex business problems.
  • Work with large-scale structured and unstructured datasets, applying data cleansing, preprocessing, and feature engineering techniques to improve model performance.
  • Implement and maintain efficient data, model, and knowledge storage solutions to support scalable AI applications and retrieval capabilities.
  • Collaborate with data engineers, architects, and business stakeholders to design, develop, and deploy enterprise-grade AI solutions.
  • Evaluate model performance and communicate the quality, effectiveness, and business value of AI solutions to stakeholders.
  • Ensure AI solutions comply with enterprise security, governance, and Responsible AI standards.
  • 4-7 years of experience in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, Analytics, or related technical fields.
  • Hands-on experience designing and deploying AI/ML solutions in enterprise or consulting environments.
  • Strong programming skills in Python and experience with machine learning frameworks such as Tensor Flow, PyTorch, Scikit-learn, or equivalent technologies.
  • Experience with Deep Learning, Generative AI, Large Language Models (LLMs), and advanced analytics solutions.
  • Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform and their AI/ML services.
  • Experience building data pipelines and implementing MLOps practices for model deployment and operationalization.
  • Strong understanding of data preprocessing, model evaluation, optimization, and performance tuning techniques.
Preferred Qualifications
  • Experience developing and deploying Generative AI, LLM-based applications, and intelligent automation solutions.
  • Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and AI orchestration frameworks.
  • Experience with containerization technologies such as Docker and orchestration platforms such as Kubernetes.
  • Familiarity with edge AI deployments, distributed computing environments, and High-Performance Computing (HPC) architectures.
  • Experience implementing AI observability, model monitoring, and production support capabilities.
  • Strong analytical, problem-solving, and stakeholder management skills.
  • Relevant certifications in Artificial Intelligence, Machine Learning, Data Science, Cloud Platforms, or related technologies are preferred.
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