S&C Global Network - AI - Managed Services ML Engineering Consultant

Job Description

Entity :- Accenture Strategy & Consulting Team :- Global Network Data & AI Practice :- AI Managed Services Title: - AI LLM Technology Architecture Consultant Role :- ML Engineering Consultant Job Location:- Hyderabad Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition As part of our Data & AI practice, you will join a worldwide network of smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. WHAT'S IN IT FOR YOU? An opportunity to work on high-visibility projects with top clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everything"from how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. What you would do in this role Hands on experience on ML Services of AWS or Azure or Google. Develop, train, and deploy machine learning models for real-world applications. Design and implement data pipelines for model training and inference. Conduct model evaluation, testing, and validation to ensure robustness and accuracy. Work with large-scale datasets to build and improve predictive models. Optimize and fine-tune ML algorithms for performance, scalability, and efficiency. Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into production systems. Stay up-to-date with the latest trends and advancements in machine learning and AI. Write clean, maintainable, and well-documented code.