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Senior Machine Learning Engineer, Developer Advocacy
Summary by AIEngineer.careers
Senior Machine Learning Engineer, Developer Advocacy is a Machine Learning Engineer role (full-time). with Grafana Labs. in REMOTE, IRELAND (REMOTE), IE. Compensation shown: $112K–$135K (est.). Imported listing (source: jquasar.42web.io). Apply on the employer's site (jquasar.42web.io).
Imported listing (source: jquasar.42web.io) · Apply on jquasar.42web.io
REMOTE · IRELAND (REMOTE) · IE
$112K–$135K (est.)
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from jquasar.42web.io
Grafana Labs is seeking a Senior Machine Learning Engineer focused on Developer Advocacy to transform an interactive learning platform into a personalized, real-time recommendation system. The role involves designing and implementing ML-driven features while actively engaging with the developer community. This position offers fully remote work restricted to candidates residing in Ireland.
Responsibilities
- Lead the evolution of interactive learning tools into real-time recommendation systems
- Design and implement machine learning models for personalized user experiences
- Collaborate on developer advocacy initiatives and technical content creation
- Optimize ML pipelines for scalability and low-latency inference
Requirements
- Proven experience as a Machine Learning Engineer or similar role
- Strong background in building and deploying recommendation systems
- Experience with developer advocacy, technical writing, or community engagement
- Proficiency in Python and modern ML frameworks
Nice to Have
- Familiarity with observability, metrics, or time-series data platforms
GL
Grafana Labs
New York · US · 1436+ employees
Grafana Labs provides an open-source observability platform that allows users to monitor, visualize, and analyze their data across various systems and infrastructure. Their flagship product, Grafana, is widely used for creating dashboards and understanding disparate data sources at scale.
