AI/ML Engineer
Core
Design, build, and maintain AI/ML lifecycle core services, orchestration capabilities, and infrastructure for training, validating, and deploying machine learning models.
Role type
AI/ML Engineer (Infrastructure & MLOps)
Builds
Reusable components, libraries, model serving platforms, automated ML pipelines, and monitoring systems.
Domain
Artificial Intelligence / Machine Learning / MLOps
Deliverable
production ML models
Required skills
AI/ML algorithm optimization, MLOps practices, automated pipeline implementation, model monitoring, model explainability, version control, testing frameworks, collaboration with data engineers
Preferred skills
Technical guidance to data scientists, system documentation, troubleshooting complex AI/ML issues
Technologies
(Not explicitly listed)
Responsibilities
Design and implement infrastructure for training and deploying ML models; develop tools for model explainability; optimize algorithms for performance and scalability; implement MLOps for CI/CD; collaborate with data engineers on data pipelines; troubleshoot complex system issues.
Seniority
Multiple levels (Junior, Journeyman, Senior)
