Senior Machine Learning Engineer (Developer Advocacy)

About the role

Join Grafana Labs as a Senior Machine Learning Engineer (Developer Advocacy) and lead the evolution of our Interactive Learning system. You will build, deploy, and operate recommendation models, design experiments, and establish evaluation methodology. Collaborate closely with software engineers and data analysts to productionize models and integrate them into the recommender service. Enjoy a fully remote work environment, generous vacation, healthcare coverage, retirement planning, and professional development opportunities. Key missions: Evoluer le système de recommandation du plugin d'apprentissage interactif, en développant des approches de plus en plus personnalisées pour la sélection, le classement et la recommandation d'actions.. Construire, déployer et exploiter des modèles de recommandation, concevoir des expériences, établir une méthodologie d'évaluation et définir la feuille de route scientifique.. Collaborer avec des ingénieurs logiciels et des analystes de données pour produire des modèles et les intégrer en toute sécurité dans le service de recommandation. Profile: - Recommendation and personalization science: you have built recommendation, ranking, search, matching, propensity, or next-best-action systems. You are comfortable beginning with simple, explainable approaches when they are the best way to learn - Experience with SaaS product telemetry and customer-account data - Experience using warehouse-scale behavioral data - Applied model ownership. You have personally built, validated, monitored, and iterated on models used in a product or operational environment. You can work effectively in version-controlled codebases and collaborate with engineers on production implementation - HTTP/gRPC, streaming, Go/TypeScript previous experience in distributed systems - You should also be a strong product thinker and technical communicator - Experience with directed graphs, sequence models, or prerequisite-aware recommendations - Experience with contextual bandits or other exploration strategies - You can take an ambitious and ambiguous objective, identify the most important unknowns, and create a sequence of models and experiments that steadily improves the product - We are looking for someone who can understand the whole problem, establish strong foundations, and ship measurable improvements into the existing recommender one iteration at a time - Experience with content, education, onboarding, or learning recommendation systems - Familiarity with Grafana or the broader observability ecosystem - We know it is rare to find everything. Strong candidates should demonstrate credible ability across all three core areas below and be particularly strong in at least two - Experience with open source software or transparent development practices - Experience working with privacy, fairness, explainability, or responsible personalization constraints