Senior Machine Learning Engineer (Recommender Systems, Developer Advocacy)

TL;DR

Senior Machine Learning Engineer (Recommender Systems, Developer Advocacy): Building and operating a personalized recommendation system inside an interactive learning experience, with an accent on real-time candidate selection, ranking, sequencing, and next-best-action recommendations. Focus on evolving applied recommendation models end-to-end—training, serving, evaluation, monitoring, and shipping measurable improvements through experimentation and offline/online/longitudinal metrics.

Location: United Kingdom (fully remote)

Salary: GBP 91,755 - GBP 110,106 base compensation (country-specific), plus RSUs

Company

hirify.global builds an open observability cloud and an open-source, in-product learning experience for Grafana users.

What you will do

• Evolve the Interactive Learning recommender: develop personalized approaches for candidate selection, ranking, sequencing, and next-best-action recommendations.
• Own a real-time recommendation service and the full applied model lifecycle: develop, validate, version, monitor, and iterate on models used in production.
• Define recommendation quality with offline, online, and longitudinal measures; build feature pipelines and monitor model performance and architecture.
• Ship incremental improvements by integrating new instrumentation and platform capabilities into the existing recommender iteratively.
• Partner with software engineers and data analysts to productionize models safely and integrate them into the recommender service.
• Translate ambiguous product needs into testable hypotheses and measurable experiment outcomes; communicate modeling choices, tradeoffs, uncertainty, and results to technical and non-technical stakeholders.

Requirements

• UK-based candidates only for this fully remote role.
• Experience building recommendation/personalization systems (recommendation, ranking, matching, propensity, or next-best-action) and comfort starting with simple explainable approaches when appropriate.
• Hands-on experience with HTTP/gRPC, streaming, and distributed systems; prior experience with Go and/or TypeScript.
• Applied model ownership: personally built, validated, monitored, and iterated on models used in a product or operational environment; able to work in version-controlled codebases and collaborate with engineers on production implementation.
• Strong product thinking and technical communication to define unknowns, plan experiments, and steadily improve the product.

Nice to have

• Experience with learning/content/onboarding recommendation systems.
• Experience with SaaS telemetry and customer-account data; warehouse-scale behavioral data.
• Experience with directed graphs, sequence models, prerequisite-aware recommendations, contextual bandits, or exploration strategies.
• Familiarity with Grafana or the observability ecosystem.
• Experience with open source practices and responsible personalization (privacy, fairness, explainability).

Culture & Benefits

• 100% remote company with a global culture and collaboration across 40+ countries.
• Restricted Stock Units (RSUs) for ownership and shared outcomes.
• Global annual leave policy of 30 days, including Grafana Shutdown Days.
• Transparent communication, autonomy, and high-trust, low-ego teams focused on outcomes.
• In-person onboarding for new hires to learn how work is done.

Hiring process

• Interview process includes compensation/level assessment and evaluation of applied recommendation/model ownership and technical communication.
• Recruitment may use AI tools to help match CV information to job postings, with manual review by the team.