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

EY · Jacksonville, FL · 2 wk ago

On-siteInformation Technology$66k–$134k/yrFull-time

About the role

EY is the only professional services firm with a separate business unit ("FSO") that is dedicated to the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry. This practice also has several Service Delivery Centers that are made up of high-performing US-based resources who work closely with our experienced client-serving professionals to deliver project-based work and managed services to our US-based Financial Services clients.

Responsibilities

Build Autonomous Financial AI Systems
Design and implement multi-agent architectures using LangChain, AutoGen, or CrewAI for complex financial workflows
Deploy production-ready LLMs fine-tuned for financial domain expertise (loan underwriting, risk assessment, regulatory compliance)
Create RAG (Retrieval-Augmented Generation) systems that connect AI agents to enterprise knowledge bases and real-time market data
Implement agentic reasoning systems capable of autonomous decision-making within regulatory boundaries
Scale AI Solutions for Enterprise Impact
Deploy AI agents serving millions of customers with sub-second latency requirements
Build robust MLOps pipelines for continuous model improvement and A/B testing
Implement comprehensive monitoring and observability for autonomous systems
Optimize inference costs while maintaining performance SLAs
Drive Innovation in Financial AI
Prototype breakthrough applications: AI-powered trading assistants, autonomous compliance monitors, intelligent fraud detection agents
Collaborate with financial domain experts to translate complex regulations into AI agent behaviors
Contribute to EY’s AI research initiatives and patent applications
Present solutions to C-suite executives at major financial institutions

Requirements

Core Skills (Must-Have): 3-5 years of Python programming with production deployment experience, hands-on experience with LLMs, agentic AI frameworks, vector databases, cloud platforms, and MLOps practices
Preferred Skills (Nice-to-Have): Experience with financial services applications, knowledge of prompt engineering and in-context learning optimization, familiarity with model fine-tuning techniques, understanding of AI safety practices, experience with real-time streaming architectures, contributions to open-source AI projects, good written and verbal communication skills, willingness and ability to travel at 0%-25%, valid driver’s license in the US, valid passport

Qualifications

Ideal Qualifications: Certification in any database management system, reporting or data visualization, or programming/statistical language, working knowledge or certifications in cloud technologies, experience with generative AI models and techniques, understanding of the ethical implications of generative AI and commitment to responsible AI practices

Skills

Core Skills: Python programming, LLMs, agentic AI frameworks, vector databases, cloud platforms, MLOps practices
Preferred Skills: Experience with financial services applications, knowledge of prompt engineering and in-context learning optimization, familiarity with model fine-tuning techniques, understanding of AI safety practices, experience with real-time streaming architectures, contributions to open-source AI projects, good written and verbal communication skills, willingness and ability to travel at 0%-25%, valid driver’s license in the US, valid passport

Benefits

Comprehensive compensation and benefits package including medical and dental coverage, pension and 401(k) plans, a wide range of paid time off options, and opportunities to develop new skills and progress your career.

Pay

The base salary range for this job in all geographic locations in the US is $65,500 to $134,000. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $78,600 to $152,100. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Schedule

Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.