AI/ML Associate Manager

Accenture Middle East; Riyadh; On-site; SAR 360,000 - 600,000; Full time

Job summary

Accenture Middle East is seeking an AI/ML Engineer Associate Manager to design, build, and deploy scalable AI/ML solutions leveraging cloud-native services, Generative AI, and MLOps.

You will lead data pipelines, model deployment, monitoring, and governance across cloud, edge, and HPC environments, and collaborate with architects and stakeholders to deliver enterprise-grade AI.

The role emphasizes security, Responsible AI, and continuous improvement of platforms.

Qualifications

• 6–9 years of AI/ML experience in technical fields.
• Hands-on experience designing, developing, and deploying AI/ML solutions in enterprise environments.
• Strong Python programming and experience with TensorFlow, PyTorch, Scikit-learn, or equivalent.
• Knowledge of cloud platforms (Azure/AWS/GCP) and their AI/ML services.

Responsibilities

• Design and develop AI/ML solutions using modern frameworks and cloud-based services.
• Build, deploy, and maintain scalable data pipelines for training, inference, monitoring, and production operations.
• Implement DevOps and MLOps practices for model deployment, versioning, and lifecycle management.
• Customize and deploy Generative AI and LLM solutions to meet business requirements.
• Collaborate with architects, data engineers, and stakeholders to deliver enterprise-grade AI solutions.

Skills

Python

TensorFlow/PyTorch

Cloud platforms

MLOps

Data pipelines

LLMs/Generative AI

Docker/Kubernetes

Tools

Docker

Kubernetes

ML frameworks

Job description

Role Overview

As an AI/ML Engineer Associate Manager, you will design, build, and deploy scalable Artificial Intelligence (AI) and Machine Learning (ML) solutions that enable organizations to unlock value from data and advanced analytics. You will leverage cloud-native AI services, Generative AI technologies, and MLOps best practices to deliver production-ready solutions while driving innovation through research, model development, and high-performance computing capabilities.

Key Responsibilities

• Design and develop AI and Machine Learning solutions using modern AI frameworks and cloud-based AI services.
• Build, deploy, and maintain scalable data pipelines that support model training, inference, monitoring, and production operations.
• Implement DevOps and MLOps practices to ensure efficient model development, deployment, versioning, and lifecycle management.
• Customize, fine-tune, and deploy Deep Learning, Generative AI, and Large Language Model (LLM) solutions to address business requirements.
• Develop AI solutions that can operate across cloud environments, edge devices, and High-Performance Computing (HPC) infrastructures.
• Evaluate model performance and communicate the quality, scalability, and business value of AI solutions to stakeholders.
• Conduct research and development activities focused on emerging AI technologies, algorithms, simulations, and advanced analytical methods.
• Work with large-scale structured and unstructured datasets, applying data cleansing, preprocessing, feature engineering, and optimization techniques.
• Design and implement efficient data, model, and knowledge storage mechanisms to support AI applications and retrieval capabilities.
• Collaborate with architects, data engineers, and business stakeholders to deliver robust, enterprise-grade AI solutions.
• Ensure adherence to security, governance, and Responsible AI principles throughout the AI solution lifecycle.
• Support continuous improvement of AI platforms, tools, and engineering practices to enhance solution performance and reliability.

Basic Qualifications

• 6-9 years of experience in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or related technical fields.
• Hands‑on experience designing, developing, and deploying AI/ML solutions in enterprise environments.
• Strong programming experience in Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent technologies.
• Experience working 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 scalable data pipelines and implementing MLOps practices for model deployment and monitoring.
• Strong understanding of data engineering, data preprocessing, feature engineering, and model optimization techniques.

Preferred Qualifications

• Experience developing and deploying Generative AI solutions, foundation models, and LLM-based applications.
• 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 architectures, and High-Performance Computing (HPC) environments.
• Experience implementing AI observability, model monitoring, and production support processes.
• Strong analytical, problem-solving, and stakeholder management skills.
• Relevant certifications in Artificial Intelligence, Machine Learning, Data Engineering, or Cloud Technologies are preferred.