MLOps / AI Platform Engineer

Accenture Southeast Asia; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

Accenture Southeast Asia in Kuala Lumpur seeks an AI/ML engineer to design and develop AI and ML systems, leveraging cloud AI services and scalable architectures. You will build data pipelines with DevOps & MLOps to support training and production.

You will customize deep learning and Gen AI models to meet business needs, handle edge devices and HPCs, and work with large data sets to ensure high-quality inputs for training and production.

Responsibilities

• Design and develop AI and ML systems leveraging existing cloud AI services.
• Design and build scalable data pipelines to support model training and production with DevOps & MLOps.
• Customize and apply Deep Learning and Gen AI models for use cases based on the business needs, data availability, system and infrastructure requirements including edge devices and HPCs.
• Justify the quality and value of the solution.
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex problems.
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production.
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.

Job description

• Design and develop artificial intelligence (AI) and machine learning (ML) systems leveraging existing cloud AI services.
  
• Design and build scalable data pipelines to support model training and production with DevOps & MLOps.
  
• Customize and apply Deep Learning and Gen AI models for use cases based on the business needs, data availability, system and infrastructure requirements including edge devices and High Performance Computers (HPCs).
  
• Justify the quality and value of the solution.
  
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex problems.
  
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production.
  
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.