Senior AI & ML Engineering Consultant

Ernst & Young Oman; Honolulu (HI); On-site; USD 126,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation

Medical benefits

Job summary

EY in the United States is seeking a Manager in Model Engineering to lead AI workstreams, design scalable AI/ML solutions, and guide cross-functional teams across data science and software engineering for diverse client engagements.

You will partner with clients to deliver responsible, production-ready solutions on cloud and on‑premises, mentor engineers, and ensure high-quality outcomes across analytics, data pipelines, and MLOps.

Qualifications

• Bachelor’s degree required (4-year)
• 6‑10 years of relevant experience in AI, Data Science, and/or Machine Learning
• 2‑4 years of experience directly managing technical teams
• Strong skills in Python
• Experience designing and deploying production AI/ML solutions on major cloud platforms
• Proficient in foundation models, generative AI, and agentic AI frameworks
• Experience with NLP and deep learning
• DevOps tools and CI/CD pipelines
• Experience with MLOps, LLMOps, and agentic AI workflows
• Strong communication and cross-border collaboration skills

Responsibilities

• Lead AI workstreams from solution design through production deployment
• Identify innovative solutions through research and analysis
• Manage multidisciplinary teams delivering AI engineering initiatives
• Engage with clients and lead workstreams from planning to closure
• Identify opportunities for additional services and manage engagement economics

Skills

Python

Team leadership

AI/ML

Cloud platforms

DevOps

Education

Bachelor’s degree required (4‑year)

Tools

OpenAI tools

LangChain

PyTorch

Azure DevOps

Git

Job description

EY in the United States is seeking a Manager in Model Engineering to lead AI workstreams, design scalable AI/ML solutions, and guide cross-functional teams across data science and software engineering for diverse client engagements.

You will partner with clients to deliver responsible, production-ready solutions on cloud and on‑premises, mentor engineers, and ensure high-quality outcomes across analytics, data pipelines, and MLOps.