Grafana Labs

Senior Machine Learning Engineer, Developer Advocacy| Sweden| Remote

Vaga remota de Developer Advocacy com fit claro de localização do candidato.

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Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

CanadáAlemanhaIrlandaEspanhaSuéciaReino Unido+1 mais

Salesforce TypeScript

Resumo da vaga

Senior Machine Learning Engineer, Developer Advocacy| Sweden| Remote

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Senior ML Engineer Recommender Systems, Developer Advocacy | Sweden | Remote

Evolve the Interactive Learning Plugin's recommendation system
Develop increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations.
You’ll own a real-time recommendation service
Build and operate applied models
Develop, validate, version, monitor, and iterate on models used by the recommendation system.
You’ll own model training & serving
Define what recommendation quality means
Develop offline, online, and longitudinal measures of recommendation performance.
You’ll own feature pipelines, monitoring of the model and architecture
Ship incremental improvements
Use the data and infrastructure available today while identifying the instrumentation and platform capabilities needed tomorrow.
Integrate improvements into the existing recommender rather than waiting for a complete replacement system.
Partner across disciplines
Work closely with software engineers & data analysts to productionize models and integrate them safely into the recommender service.
Partner with the Product Analytics team on metric definitions, instrumentation, data quality, dashboards, and experiment analysis.
Collaborate with Developer Advocacy, Docs, Product, Engineering, GTM, and other teams to translate ambiguous needs into testable hypotheses and measurable product decisions.
Explain modeling choices, tradeoffs, uncertainty, and results clearly to both technical and non-technical audiences.

Details

Develop increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations.
You’ll own a real-time recommendation service
Develop, validate, version, monitor, and iterate on models used by the recommendation system.
You’ll own model training & serving
Develop offline, online, and longitudinal measures of recommendation performance.
You’ll own feature pipelines, monitoring of the model and architecture
Use the data and infrastructure available today while identifying the instrumentation and platform capabilities needed tomorrow.
Integrate improvements into the existing recommender rather than waiting for a complete replacement system.
Work closely with software engineers & data analysts to productionize models and integrate them safely into the recommender service.
Partner with the Product Analytics team on metric definitions, instrumentation, data quality, dashboards, and experiment analysis.
Collaborate with Developer Advocacy, Docs, Product, Engineering, GTM, and other teams to translate ambiguous needs into testable hypotheses and measurable product decisions.
Explain modeling choices, tradeoffs, uncertainty, and results clearly to both technical and non-technical audiences.
100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose.
Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment.
Transparent Communication – Expect open decision-making and regular company-wide updates.
Innovation-Driven – Autonomy and support to ship great work and try new things.
Open Source Roots – Built on community-driven values that shape how we work.
Empowered Teams – High trust, low ego culture that values outcomes over optics.
Career Growth Pathways – Defined opportunities to grow and develop your career.
Approachable Leadership – Transparent execs who are involved, visible, and human.
Passionate People – Join a team of smart, supportive folks who care deeply about what they do.
In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.
Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable.

Senior ML Engineer Recommender Systems, Developer Advocacy | Sweden | Remote

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.
HTTP/gRPC, streaming, Go/TypeScript previous experience in distributed systems
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.

Senior ML Engineer Recommender Systems, Developer Advocacy | Sweden | Remote

Experience with content, education, onboarding, or learning recommendation systems
Experience with SaaS product telemetry and customer-account data
Experience using warehouse-scale behavioral 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

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