Senior Machine Learning Engineer, Developer Advocacy

Grafana Labs

Senior Machine Learning Engineer leading the development of personalized recommendation systems for Grafana Labs' Interactive Learning platform. Focus on building applied models and integrating features across teams.

Posted 7/22/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $154,445 - $185,334 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in recommendation and personalization science, with a strong focus on building and operating machine learning models for real-time recommendation services. Proven ability to define quality measures and collaborate across teams for effective integration.

Highest-signal resume keywords

Recommendation SystemsMachine Learning ModelsReal-Time Recommendation ServicesDistributed SystemsApplied Model Ownership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Recommendation SciencePersonalization ScienceMachine LearningModel DevelopmentQuality Measurement

Tools & Technologies

HTTPGRPCStreaming Technologies

Tech Stack

Tools & technologies

Distributed SystemsGRPC

About the role

Key responsibilities & impact

Lead the evolution of the Interactive Learning system's recommendation engine
Build and operate applied models for continuous improvement
Define measures of recommendation quality and partner across various teams for integration
Ship incremental improvements and enhance existing recommender features

Requirements

What you’ll need

Strong candidates should demonstrate credible ability across recommendation and personalization science, distributed systems, and applied model ownership
Experience with ML models, especially in recommendation systems
Familiarity with HTTP/gRPC, and streaming technologies
Comfort with ownership of real-time recommendation services

Benefits

Comp & perks

100% Remote, Global Culture
Health insurance
401(k) matching
Flexible work hours
Paid time off (30 days annual leave)
In-Person onboarding