Senior Machine Learning Engineer (Developer Advocacy)

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 with software engineers and data analysts to productionize models and integrate them into the recommender service. Enjoy benefits such as 30 days of paid vacation, health coverage, retirement planning, professional development, and a fully remote work environment.

• Evolve the Interactive Learning Plugin's recommendation system by developing increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations.
• Own a real-time recommendation service by building and operating applied models, developing, validating, versioning, monitoring, and iterating on models used by the recommendation system.
• Collaborate with cross-functional teams to productionize models and integrate them safely into the recommender service, and partner with the Product Analytics team on metric definitions, instrumentation, data quality, dashboards, and experiment analysis.
• 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
• 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
• HTTP/gRPC, streaming, Go/TypeScript previous experience in distributed systems
• 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
• You should also be a strong product thinker and technical communicator
• 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
• 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
• Experience with content, education, onboarding, or learning recommendation systems
• Experience using warehouse-scale behavioral data
• Experience with SaaS product telemetry and customer-account data
• Experience with directed graphs, sequence models, or prerequisite-aware recommendations
• Experience with contextual bandits or other exploration strategies
• Familiarity with Grafana or the broader observability ecosystem
• Experience with open source software or transparent development practices
• Experience working with privacy, fairness, explainability, or responsible personalization constraints