Customer AI Automation Architect

Role Overview: At EY, you will have the opportunity to build a unique career with global support, an inclusive culture, and advanced technology to help you become the best version of yourself. Your unique voice and perspective are essential in contributing to EY's continuous improvement. Join the team to create an exceptional experience for yourself and contribute to building a better working world for all. Key Responsibilities: - Collaborate with EY Supply Chain & Operations stakeholders and data engineering teams to ensure high-quality data curation for model training and evaluation. - Design, develop, and fine-tune Generative AI models using frameworks such as LangChain, Hugging Face, TensorFlow, or PyTorch. - Implement solutions for data pre-processing, tokenization, and dataset augmentation. - Deploy Generative AI models on cloud platforms (e.g., AWS, GCP, Azure) or edge devices for scalability and robustness. - Work on MLOps pipelines, including CI/CD workflows, model monitoring, and retraining strategies. - Conduct performance benchmarking, hyperparameter tuning, and optimization to enhance model efficiency. - Stay updated on the latest trends and advancements in Generative AI and integrate best practices into project workflows. Qualifications Required: - 6+ years of experience in Generative AI, Machine Learning, or Analytics development. - Proficiency in Python with a focus on AI/ML libraries and frameworks like LangChain, TensorFlow, PyTorch, or Hugging Face Transformers. - Experience with data pipelines and tools such as Spark, Snowflake, or Databricks. - Strong hands-on experience deploying AI models on cloud platforms like AWS SageMaker, GCP Vertex AI, or Azure ML. - Expertise in Model Development, including knowledge of LLMs (e.g., GPT-3.5, GPT-4, DALL-E, Text Embeddings Ada, LLAMA, T5, Bloom), prompt engineering, and model selection and fine-tuning techniques. - Ability to mentor developers, contribute to architectural decisions, and work on end-to-end analytics pipelines with a focus on actionable insights. - Knowledge of NLP techniques like summarization, text classification, and entity recognition. - Certifications in Machine Learning or cloud platforms are a plus. Additional Company Details: At EY, you will be part of a market-leading, multidisciplinary team of over 10,000 professionals worldwide. You will have the opportunity to work with EY GDS consulting practices globally, collaborating with leading businesses across various industries. EY is dedicated to creating a better working world by providing support, coaching, and feedback, along with opportunities for personal development and career progression in an interdisciplinary environment that emphasizes high quality and knowledge exchange. You will have the freedom and flexibility to handle your role in a way that suits you best. Role Overview: At EY, you will have the opportunity to build a unique career with global support, an inclusive culture, and advanced technology to help you become the best version of yourself. Your unique voice and perspective are essential in contributing to EY's continuous improvement. Join the team to create an exceptional experience for yourself and contribute to building a better working world for all. Key Responsibilities: - Collaborate with EY Supply Chain & Operations stakeholders and data engineering teams to ensure high-quality data curation for model training and evaluation. - Design, develop, and fine-tune Generative AI models using frameworks such as LangChain, Hugging Face, TensorFlow, or PyTorch. - Implement solutions for data pre-processing, tokenization, and dataset augmentation. - Deploy Generative AI models on cloud platforms (e.g., AWS, GCP, Azure) or edge devices for scalability and robustness. - Work on MLOps pipelines, including CI/CD workflows, model monitoring, and retraining strategies. - Conduct performance benchmarking, hyperparameter tuning, and optimization to enhance model efficiency. - Stay updated on the latest trends and advancements in Generative AI and integrate best practices into project workflows. Qualifications Required: - 6+ years of experience in Generative AI, Machine Learning, or Analytics development. - Proficiency in Python with a focus on AI/ML libraries and frameworks like LangChain, TensorFlow, PyTorch, or Hugging Face Transformers. - Experience with data pipelines and tools such as Spark, Snowflake, or Databricks. - Strong hands-on experience deploying AI models on cloud platforms like AWS SageMaker, GCP Vertex AI, or Azure ML. - Expertise in Model Development, including knowledge of LLMs (e.g., GPT-3.5, GPT-4, DALL-E, Text Embeddings Ada, LLAMA, T5, Bloom), prompt engineering, and model selection and fine-tuning techniques. - Ability to mentor developers, contribute to architectural decisions, and work on end-to-end analytics pipelines with a focus on actionable insights. - Knowledge of NLP techniques like summarization, text classification, and entity r