HubSpot logo
HubSpot

The easy-to-use CRM to scale your business.

Senior Machine Learning Engineer

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 1,001-5,000Since 2006H1B SponsorCompany SiteLinkedIn

Location

United Kingdom

Posted

113 days ago

Salary

€106.1K - €169.8K / year

Seniority

Senior

Bachelor DegreeEnglishJava

Job Description

Senior Machine Learning Engineer

HubSpot

• Design, build, and operate backend services that power context retrieval and enrichment for AI assistants and agents. • Build platform capabilities for storing, searching, and retrieving “insights” and relevant facts across HubSpot’s GTM data. • Develop systems to manage and compress context when it gets large (e.g., long contact histories, high-volume CRM data). • Create tooling that allows other engineering teams to ship assistants/agents faster, with consistent APIs and reusable primitives. • Build and maintain evaluation and measurement approaches (offline evals, golden datasets, automated metrics, human review loops) to ensure context quality and answer accuracy. • Collaborate closely with sister platform teams and downstream product engineering teams (your “customers”) to integrate platform capabilities into real experiences. • Own end-to-end delivery: architecture, implementation, observability, performance, reliability, and iteration.

Job Requirements

  • Strong track record shipping production backend systems as a senior engineer (ownership from design to delivery).
  • Professional Java experience building maintainable, testable services in production (this is core to the role).
  • Experience implementing ML workflows in production (e.g., retrieval/ranking pipelines, feature/data pipelines, model/embedding services, evaluation frameworks).
  • Comfort working with data tooling and data-intensive systems (large datasets, pipelines, and service integrations).
  • Experience operating software at meaningful scale (e.g., high throughput, significant data volume, performance and reliability constraints).
  • Strong engineering fundamentals: system design, code quality, debugging, observability, and operational excellence.

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