Senior AI/ML Engineering Consultant

EY; Greenville (SC); On-site; USD 125,000 - 251,000; Full time

Job summary

EY US is seeking a Manager in Model Engineering to lead modern AI engineering and ML initiatives alongside clients and diverse teams. You will design and build scalable AI solutions that unify varied data sources across a broad technology landscape, ensuring responsible deployment and measurable results.

You will guide production deployment, data pipelines, MLOps, and observability while collaborating with data and analytics professionals to industrialize analysis into effective strategies for

Qualifications

• Bachelor’s degree required (4-year degree).
• 6–10 years of AI, Data Science, and/or Machine Learning experience.
• 2–4 years directly managing technical teams.
• Strong Python skills.
• Experience designing and deploying production AI/ML on major cloud platforms.
• Proficiency with foundation models, generative AI, and agentic AI frameworks.
• Experience with NLP and deep learning.
• Extensive experience with DevOps tools (Git, Azure DevOps) and Agile (Jira).
• Experience with MLOps, LLMOps, and agentic AI workflows.

Responsibilities

• Lead AI workstreams from design to production deployment and optimization.
• Identify innovative solutions through research and analysis to improve processes.
• Manage multidisciplinary teams delivering complex AI initiatives with quality and responsible deployment.
• Engage with clients, lead sessions, and drive workstreams from planning to closure.
• Identify opportunities for additional services and manage engagement economics.

Skills

Python

Team leadership

Client engagement

Cross-functional collaboration

Communication

Education

Bachelor’s degree

Master’s degree (advantage)

Tools

GIT

Azure DevOps

Jira

CI/CD

scikit-learn

PyTorch

Job description

EY US is seeking a Manager in Model Engineering to lead modern AI engineering and ML initiatives alongside clients and diverse teams. You will design and build scalable AI solutions that unify varied data sources across a broad technology landscape, ensuring responsible deployment and measurable results.

You will guide production deployment, data pipelines, MLOps, and observability while collaborating with data and analytics professionals to industrialize analysis into effective strategies for