AI / ML Engineer

Intro: The AI / ML Engineer is responsible for designing, building and delivering production-ready AI applications and systems that leverage AI tools and cloud-based AI services. The role focuses on applying generative AI models and may involve deep learning, neural networks, chatbots and image processing, integrated into cloud or on-premises application pipelines. Key responsibilities: - Serve as an SME and lead design and implementation of AI-driven solutions, making team-level and cross-team decisions. - Collaborate with multiple teams, coordinate cross-functional efforts and provide solutions to problems across teams. - Build and integrate generative AI models and other ML/DL solutions into production pipelines (cloud and on-prem). - Ensure AI solutions meet production quality standards, including performance and cost-efficiency optimization. - Facilitate knowledge sharing, mentorship and professional growth within the team. Required qualifications and experience: - Minimum 5 years of experience in Google Cloud Platform Architecture; strong experience designing scalable cloud infrastructure for AI/ML workloads. - Total 15 years of full-time education is required. - Demonstrated experience with AI model deployment and lifecycle management on cloud platforms. - Familiarity with containerization and orchestration technologies to support AI application pipelines. - Experience with data processing and data integration techniques relevant to AI solutions. Technologies and skills referenced: - Google Cloud Platform, Cloud AI services, generative AI models, deep learning, neural networks, chatbots, image processing. - Containerization and orchestration (to support deployment), scalable cloud infrastructure design, model lifecycle management. Location and employment: - This is a full-time, on-site position based at Accenture's Chennai office. Notes: - "Good to have" skills are listed as NA on the posting. The role emphasizes both technical delivery and leadership/mentorship responsibilities.