Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Manager

EY is a global leader in assurance, tax, transaction, and advisory services, dedicated to the financial services marketplace. They are seeking a Machine Learning Engineer (MLE) - Manager to work with diverse teams to deliver AI and data services, solve complex problems, and help clients make data-driven decisions.

Responsibilities:

• Collaborating, mentoring, and coaching teams with diverse skills and backgrounds
• Fostering an innovative and inclusive team-oriented work environment
• Being accountable for the success of your team and the project’s components
• Building strong relationships with your internal clients
• Great communication and influencing skills
• Demonstrating in-depth technical capabilities, professional knowledge, and interest in the financial industry and technology
• Leading and managing multi-disciplinary teams through a product life cycle – requirements, design, development, and testing
• Designing, building, and maintaining production-grade ML and DL models, machine learning workflows, and pipelines
• Helping clients make data-driven decisions by working with structured and unstructured data sets and building out predictive models
• Designing and developing solutions leveraging big data technology (Hadoop, Spark, etc.) to ingest, process, and analyze large, disparate data sets

Requirements:

• A bachelor's or master's degree in computer science, information systems, or related technology majors
• Minimum of 5 years of related work experience in AI/ML engineering or MLE/ML Ops
• Experience working with business, management, and technology concepts
• Proficiency in Python programming and associated machine learning libraries/packages (sklearn, TensorFlow, PyTorch, etc.)
• Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP) for deploying and managing ML and AI solutions
• Strong deep learning experience, particularly in applications of Neural Network architectures to Natural Language Processing, Computer Vision, and Machine Intelligence
• Knowledge of MLOps practices for continuous integration and continuous deployment (CI/CD) of machine learning models in a cloud environment
• Good written and verbal communication skills
• A willingness and ability to travel at 0%-25%
• Valid driver's license in the US
• Valid passport
• Certification in any database management system, reporting or data visualization, or programming/statistical language
• Working knowledge or certifications in cloud technologies such as Snowflake, Databricks, AWS, or Azure
• Practical experience in developing and deploying Generative AI applications for various use cases such as text generation, image synthesis, and creative AI
• Familiarity with cloud-based machine learning services like AWS SageMaker, Google AI Platform, or Azure Machine Learning