AI/ML Computational Scientist Manager
Pubblicato il 06-10-2026 - Accenture in Roma
Questa posizione è in Accenture
Il processo di selezione sarà interamente gestito Accenture.
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YOU ARE
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
Compensation at Accenture varies depending on a wide array of factors including but not limited to role, level, seniority, responsibility, skillset, and level of experience. For this position, the Metalmeccanico National Collective Bargaining Agreement applies, with one of the following pay grades and corresponding gross annual salary range:
A1 (Quadro) *€50,000 - €78,500*
Dirigente *€67,400- €95,200*
THE WORK
* Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
* Develop and implement machine learning algorithms, models, and computational systems; 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 various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC
* Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
* 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 mo