Primary responsibilities include developing and maintaining infrastructure for machine learning model deployment, ensuring seamless integration of AI models into production systems, automating deployment processes, implementing end-to-end machine learning pipeline automation, and establishing continuous integration and delivery (CI/CD) infrastructure.
The ideal candidate will have a Master's degree in computer science, minimum 5 years of experience in MLOps, proficiency in programming languages like Python, Java, or Scala, expertise in cloud platforms such as Azure, AWS, or Google Cloud Platform, experience with machine learning frameworks like TensorFlow and PyTorch, and strong understanding of DevOps principles and technologies.
EY offers competitive compensation including a potential bonus, 29 vacation days, flexible working arrangements, home office setup support, laptop and smartphone provisions, professional development opportunities, vitality programs, and sustainable mobility options. The role provides an opportunity to work on cutting-edge technology projects within the financial services sector and contribute to digital transformation initiatives.
