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AI/ML Associate Manager
Accenture
Riyadh, KSA
Full-time
Senior · 6+ years experience
Onsite
Discovered 3 weeks ago
PythonTensorFlowPyTorchScikit-learnAzureAWS
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Role Overview
As an AI/ML Associate Manager , you will design, develop, and deploy advanced Artificial Intelligence (AI) and Machine Learning (ML) solutions that address complex business challenges. You will leverage cloud AI services, Generative AI technologies, and modern MLOps practices to build scalable, production-ready AI systems. This role requires expertise in model development, data engineering, and AI platform capabilities to support enterprise-wide AI adoption.
Key Skills for This Role
PythonTensorFlowPyTorchScikit-learnAzureAWS
Full Job Posting
Role Overview
As an AI/ML Associate Manager , you will design, develop, and deploy advanced Artificial Intelligence (AI) and Machine Learning (ML) solutions that address complex business challenges. You will leverage cloud AI services, Generative AI technologies, and modern MLOps practices to build scalable, production-ready AI systems. This role requires expertise in model development, data engineering, and AI platform capabilities to support enterprise-wide AI adoption.
Key Responsibilities
- Design and develop AI and Machine Learning solutions using cloud-native AI services and modern AI frameworks.
- Build and maintain scalable data pipelines to support model training, deployment, monitoring, and production operations.
- Implement DevOps and MLOps practices to enable efficient model lifecycle management and continuous delivery.
- Customize, fine-tune, and deploy Generative AI, Large Language Models (LLMs), and Deep Learning models based on business requirements.
- Develop AI solutions that operate across cloud environments, edge devices, and high-performance computing (HPC) infrastructures.
- Evaluate model performance and demonstrate the business value, accuracy, and effectiveness of AI solutions.
- Conduct research and development activities to assess emerging AI technologies, algorithms, and modeling approaches.
- Work with large-scale structured and unstructured datasets, applying data preparation and feature engineering techniques to improve model outcomes.
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