AI/ML Computational Science Senior Manager/Manager/Associate Manager/Specialist job opportunity at Accenture Plc.

Home Jobs In Australia Tag: AI & Data AI/ML Computational Science Senior Manager/Manager/Associate Manager/Specialist position at Accenture Plc


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Accenture Plc AI/ML Computational Science Senior Manager/Manager/Associate Manager/Specialist
Experience: 10 years
Pattern: full-time
Country:
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AI & Data

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degreeBachelor's (B.Sc.)
loacation Multiple Locations, Australia
loacation Multiple Locat..........Australia

About Accenture We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.At Accenture, we see well-being holistically, supporting our people’s physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We’re proud to be consistently recognized as one of the World’s Best Workplaces™.Join Accenture to work at the heart of change. Visit us at www.accenture.com Role: AI/ML Computational Science Senior Manager / Manager / Associate Manager / Specialist Role Purpose: Develop and Deploy machine learning (ML) and artificial intelligence (AI) solutions, ensuring alignment with strategic business objectives. Build scalable pipelines, optimise model performance, and manage end-to-end AI/ML workflows, including data preprocessing, model development, testing, deployment, and monitoring. Role Responsibilities: Design, train, and deploy ML/AI models using robust pipelines for data processing, feature engineering, training, evaluation, and deployment Leverage cloud platforms (AWS, Azure, GCP) to build and manage scalable infrastructure, ensuring automation through DevOps (CI/CD) principles Monitor and retrain models to maintain performance and resilience within the ML-Ops lifecycle Develop advanced AI/ML systems, including Deep Learning and Generative AI, for diverse applications like edge devices and HPCs Collaborate with cross-functional teams to accelerate the delivery of efficient, scalable AI solutions while integrating cutting-edge research and innovation

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