AI/ML Engineering Manager — Client-Focused Solutions

Ernst & Young Oman; Stamford (CT); Remote; USD 126,000 - 230,000; Full time

Job summary

EY is seeking a Manager in Model Engineering to lead modern AI/ML solutions, working with clients and cross‑functional teams to design, build, and deploy high‑impact AI systems across cloud and on‑prem environments.

You will guide analysts and engineers, ensure responsible deployment, and drive continuous improvement in data pipelines, models, and analytics solutions while collaborating with diverse, global teams.

Qualifications

• Bachelor’s degree required (4-year).
• 6–10 years of AI, data science and/or machine learning experience.
• 2–4 years of experience directly managing technical teams.
• Strong Python skills.
• Experience designing and maintaining production AI/ML on major cloud platforms.
• Proficiency with foundation models and generative AI frameworks.
• Experience with NLP and deep learning.
• DevOps, CI/CD, Jira, and Agile methodologies.
• 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.
• Manage multidisciplinary teams delivering complex AI engineering initiatives.
• Engage with clients, run daily sessions, and guide workstreams from planning to closure.
• Identify opportunities for additional services and manage engagement economics.

Skills

Python

Cloud platforms

DevOps

MLOps

LLMOps

Retrieval Augmented Generation

PyTorch

scikit-learn

SQL

Pandas

Spark

NLP

Data modeling

Software engineering

Communication

Education

Bachelor's degree

Tools

OpenAI

DALL-E

Langchain

Azure DevOps

Git

Jira

CI/CD pipelines

PyTorch

Job description

EY is seeking a Manager in Model Engineering to lead modern AI/ML solutions, working with clients and cross‑functional teams to design, build, and deploy high‑impact AI systems across cloud and on‑prem environments.

You will guide analysts and engineers, ensure responsible deployment, and drive continuous improvement in data pipelines, models, and analytics solutions while collaborating with diverse, global teams.