Senior AI/ML Engineer — Enterprise AI, Knowledge Graph & MLOps

CBRE; Columbus (OH); On-site; USD 235,000 - 255,000; Full time

Benefits offered by this job

Discretionary bonus

Job summary

CBRE is seeking a Senior AI/ML Engineer to design, build, and operationalize production-grade AI systems powering enterprise intelligence. You will own end-to-end deliverables in a fast-paced, business-facing environment.

You’ll drive agentic workflows, knowledge graph ontology, and ML model pipelines while collaborating with product managers and stakeholders to deliver measurable client and portfolio insights.

Qualifications

• 5+ years of professional experience in AI/ML engineering with production deployments.
• Demonstrated track record of shipping AI/ML systems in fast-moving environments.
• Experience working with product managers or business stakeholders, not just engineers.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related quantitative field.

Responsibilities

• Design and implement agentic AI frameworks including multi-agent orchestration and autonomous task execution systems.
• Build and optimize RAG pipelines and memory systems for enterprise scale.
• Integrate LLM-powered agents with internal APIs, databases, and business systems to automate complex workflows.
• Contribute to knowledge graph design, ontology development, and entity relationship modeling.
• Design, train, evaluate, and deploy ML models for predictive analytics and anomaly detection.

Skills

AI/ML engineering

Python

LLM architectures

MLOps

Knowledge graph

Stakeholder collaboration

Production deployments

Education

Bachelor’s or Master’s degree in CS/Data Science/Engineering

Tools

Docker

Kubernetes

PyTorch

TensorFlow

HuggingFace

Azure ML

AWS SageMaker

GCP Vertex AI

Job description

CBRE is seeking a Senior AI/ML Engineer to design, build, and operationalize production-grade AI systems powering enterprise intelligence. You will own end-to-end deliverables in a fast-paced, business-facing environment.

You’ll drive agentic workflows, knowledge graph ontology, and ML model pipelines while collaborating with product managers and stakeholders to deliver measurable client and portfolio insights.