AI & Machine Learning Engineering Consultant - Manager - Consulting - Location OPEN

About the position Our Artificial Intelligence and Data team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions. In this role, you will research, build, and implement scalable artificial intelligence systems that learn and make predictions tailored to business requirements across various environments, including cloud and on-premises. You will enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions. As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients. You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry. Responsibilities • Leading workstream delivery and ensuring the effective management of processes and projects. • Continuously improving processes by identifying innovative solutions through research and analysis. • Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results. • Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure. • Identifying opportunities for additional services and managing engagement economics. Requirements • A Bachelor's degree required (4-year degree). • 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning • 2-4 years of experience directly managing technical teams • Strong skills in Python • Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams • Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform • Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch • Experience with natural language processing and deep learning • Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and Jobmatrixo/CD pipelines for developing, deploying, and scaling analytical solutions • Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation • Experience with model retraining and feedback loop methodologies • Experience with model and solution monitoring and reporting • Understanding of data structures, data modelling and software engineering best practices • Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques • Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements • Skills in Technical Design Optimization • Strong relationship-building skills • Demonstrated client trust and value • Digital fluency and emotional agility • Commercial acumen and negotiation skills • Proven ability to lead teams and manage change Nice-to-haves • A deep understanding of and ability to t

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