About the position At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunityOur 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. Additionally, you will engage with life sciences stakeholders to understand their unique challenges and tailor AI solutions accordingly. As a Senior AI Native Engineer, you will be at the forefront of revolutionizing how businesses leverage artificial intelligence. Your role will involve researching, building, and implementing scalable AI systems that learn and make predictions tailored to diverse business environments, whether in the cloud or on-premises. You will enhance data pipelines to ensure data integrity and optimize learning processes, all while collaborating with a talented team of data and analytics professionals. Additionally, you will apply your engineering expertise to develop AI and data solutions that support key life sciences needs across scientific, clinical, and commercial domains. Your key responsibilitiesIn this role, you will contribute significantly to the delivery of innovative AI solutions. 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 • Researching and implementing scalable AI systems that meet business requirements. • Enhancing data pipelines and storage for optimal data accuracy and cleanliness. • Monitoring and optimizing learning processes to improve high-performance models. • Developing AI and data engineering solutions for life sciences by understanding sector‑specific datasets such as commercial, clinical, and R&D data, and aligning technical approaches to these needs. • This position may have travel requirements as needed to engage with external clients regularly. Requirements • A Bachelor’s degree required (4-year degree). • 3-6 years of full-time working experience in AI and/or Machine Learning • Strong skills in Python • Ability to 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 CI/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 • Familiarity with the types of data used across pharmaceutical commercial, clinical, and R&D f