Salary
≈ $67k – $138k per year (Estimated)
Location
Remote (United States, Canada, ET hours)also open in France, Germany, Netherlands, Sweden, United Kingdom
Employment
Contractor
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 21, 2026. Mozilla Corporation scores A on the Alion truth index.
Overview
Company
Impact
Profile match
Mozilla Corporation is the commercial subsidiary of the non-profit Mozilla Foundation, created in 2005 to develop and distribute Firefox and related products. It is unusual in structure: profits flow back to the foundation rather than to shareholders, and the great majority of revenue has historically come from a single search default agreement, most recently with Google. Headquartered in Mountain View with a largely distributed workforce, it has been trying to reduce that dependence through advertising products, a virtual private network, the data removal service Monitor and its Anonym advertising measurement business.
Backed by UpWest, Trinity Ventures, Yegor256
The role
You will build and improve the WebCompat team’s internal tooling, the dashboards and the broken-site-report screenshot pipeline the team relies on to triage and prioritize site breakage. This is a focused tooling role that makes the WebCompat program faster and more data-driven.
*This role will be Remote and must be located in Eastern Time Zone in US or Canada
Responsibilities
- Build and improve WebCompat dashboards (triage, reporting, and metrics).
- Improve the broken-site-report screenshot capture and pipeline.
- Work with the WebCompat team (including QA) to turn reporting and triage needs into reliable tooling.
Required qualifications
- Solid web development (JavaScript, HTML, CSS, Python & Django) and experience building dashboards / data views.
- Comfort with tooling, automation, and web services.
- Self-directed, with good written communication.
Preferred
- Familiarity with WebCompat workflows and Bugzilla.
- Experience with screenshot / automation pipelines.
- Experience with Machine Learning
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