This role spearheads the end-to-end productionalization of AI initiatives across Gartner by establishing resilient MLOps and LLMOps pipelines
Job Summary
This role spearheads the end-to-end productionalization of AI initiatives across Gartner by establishing resilient MLOps and LLMOps pipelines.
The successful candidate will mentor engineering teams, define best practices for model lifecycle management, and drive the integration of advanced analytics into core business processes.
Gartner offers a competitive salary range of $116,000 - $170,000 USD along with extensive benefits including unlimited growth opportunities and a hybrid work environment.
Matching Summary
This role spearheads the end-to-end productionalization of AI initiatives across Gartner by establishing resilient MLOps and LLMOps pipelines.
Salary
Base: $116,000 - $170,000 USD; Bonus: Annual bonus plan or uncapped sales incentive; Benefits: 401k match up to $7,200, PTO, stock purchase plan
Skills & Requirements
Must-have
4+ years AI/ML engineering experience
MLOps and LLMOps platform proficiency
Python programming with ML frameworks
Docker and Kubernetes containerization
Cloud platform expertise AWS Azure GCP
Infrastructure as code Terraform CloudFormation
Nice-to-have
Experience deploying Large Language Models
Knowledge of AI governance and explainability
Familiarity with vector databases and RAG
Background in Agile/Scrum methodologies
Exposure to edge computing optimization
Key Requirements
4+ years progressive experience in AI/ML engineering