Grafana Labs

2 days ago

Senior Machine Learning Engineer, Developer Advocacy | Sweden | Remote

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Build and operate applied recommendation models for an open-source Interactive Learning experience. Evolve rule-based recommendations into a continuously improving system driven by real-time behavior, content metadata, customer context, and experimentation. Own the model lifecycle (training, validation, monitoring, serving), define recommendation quality with offline/online/longitudinal measures, and ship incremental improvements in collaboration with software engineers and product analytics.

Location: Sweden

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Evolve the Interactive Learning Plugin recommendation system into increasingly personalized next-best-action recommendations (candidate selection, ranking, sequencing).
•Develop, validate, version, monitor, and iterate on models powering the recommendation system, including model training and serving.
•Define recommendation quality with offline, online, and longitudinal performance measures, and own feature pipelines and monitoring.
•Ship incremental improvements by integrating with the existing recommender system while extending instrumentation and platform capabilities.
•Partner with software engineers, data analysts, and product analytics to productionize models, define metrics/instrumentation, and translate needs into testable hypotheses.
•Explain modeling choices, tradeoffs, uncertainty, and results to technical and non-technical audiences.

Pay and Benefits

Salary: SEK 775,444 - 930,533

Equity and Bonus:Equity

Perks:RsusAnnual LeavePaid Leave

Key Requirements

•Built recommendation, ranking, search, matching, propensity, or next-best-action systems, with comfort starting from simple explainable approaches when appropriate.
•Experience with HTTP/gRPC, streaming, and Go/TypeScript in distributed systems.
•Personally owned applied models end-to-end (built, validated, monitored, iterated) in a product or operational environment, working in version-controlled codebases.
•Can take ambiguous objectives, identify key unknowns, and create a sequence of models and experiments that steadily improves the product.
•Experience with content/learning recommendation systems, SaaS telemetry, warehouse-scale behavioral data, and/or responsible personalization constraints is a plus.

Experience:Open sourceRecommendation systemsSaaSTelemetryDistributed systemsObservability

Skills:Product thinkingTechnical communicationCollaborationScientific problem solving

Languages:English

Tech Stack:HTTPGRPCStreamingGoTypeScriptRecommendationRankingSearchMatchingPropensityNext-best-actionExperimentationFeature pipelinesMonitoringModel trainingModel servingDirected graphsSequence modelsContextual banditsSaaS telemetry

Company Brief

Grafana Labs

Develops open-source and commercial observability tools, including Grafana for metrics visualization, Loki for log aggregation, and Tempo for tracing, enabling organizations to monitor, analyze, and visualize system performance and telemetry data.

Industry: Developer Tools

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: New York, United States

Founded: 2014

Website LinkedIn

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Grafana Labs

2 days ago

Senior Machine Learning Engineer, Developer Advocacy | Sweden | Remote

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: Sweden

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Evolve the Interactive Learning Plugin recommendation system into increasingly personalized next-best-action recommendations (candidate selection, ranking, sequencing).
•Develop, validate, version, monitor, and iterate on models powering the recommendation system, including model training and serving.
•Define recommendation quality with offline, online, and longitudinal performance measures, and own feature pipelines and monitoring.
•Ship incremental improvements by integrating with the existing recommender system while extending instrumentation and platform capabilities.
•Partner with software engineers, data analysts, and product analytics to productionize models, define metrics/instrumentation, and translate needs into testable hypotheses.
•Explain modeling choices, tradeoffs, uncertainty, and results to technical and non-technical audiences.

Pay and Benefits

Salary: SEK 775,444 - 930,533

Equity and Bonus:Equity

Perks:RsusAnnual LeavePaid Leave

Key Requirements

•Built recommendation, ranking, search, matching, propensity, or next-best-action systems, with comfort starting from simple explainable approaches when appropriate.
•Experience with HTTP/gRPC, streaming, and Go/TypeScript in distributed systems.
•Personally owned applied models end-to-end (built, validated, monitored, iterated) in a product or operational environment, working in version-controlled codebases.
•Can take ambiguous objectives, identify key unknowns, and create a sequence of models and experiments that steadily improves the product.
•Experience with content/learning recommendation systems, SaaS telemetry, warehouse-scale behavioral data, and/or responsible personalization constraints is a plus.

Experience:Open sourceRecommendation systemsSaaSTelemetryDistributed systemsObservability

Skills:Product thinkingTechnical communicationCollaborationScientific problem solving

Languages:English

Company Brief

Grafana Labs

Industry: Developer Tools

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: New York, United States

Founded: 2014

Website LinkedIn