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

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: GPT-4, Claude, Llama, or similar foundation models
• - Agentic AI frameworks: LangChain, AutoGen, CrewAI, or similar multi-agent orchestration tools
• - Vector databases: Pinecone, Weaviate, or Chroma for semantic search at scale
• - Cloud platforms: AWS SageMaker, Azure OpenAI Service, or Google Vertex AI
• - MLOps practices: Model versioning, A/B testing, drift detection, and continuous deployment

Preferred Skills

• Nice-to-Have
• - Experience with financial services applications (trading, risk, compliance, or banking)
• - Knowledge of prompt engineering and in-context learning optimization
• - Familiarity with model fine-tuning techniques (LoRA, QLoRA, PEFT)
• - Understanding of AI safety practices and responsible AI frameworks
• - Experience with real-time streaming architectures (Kafka, Flink)
• - Contributions to open-source AI projects
• - Good written and verbal communication skills
• - A 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 such as Snowflake, Databricks, AWS, or Azure
• - Experience with generative AI models and techniques, including GANs and Transformers
• - Understanding of the ethical implications of generative AI and commitment to responsible AI practices

Benefits

Our Total Rewards package includes medical and dental coverage, both pension and 401(k) plans, a minimum of 15 days of vacation plus ten observed holidays and three paid personal days, and a range of programs and benefits designed to support your physical, financial, and social well-being.

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

We offer a flexible vacation policy where you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.