Web Browser Researcher
US$174,000 – US$235,000 / yr base salary
Posted 15 Oct 2026
Advertised as “Senior Web Browser Researcher”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- People management
- Employment
- Remote
- Visa sponsorship
- Not offered
| Base salary | US$174,000 – US$235,000 / yr |
|---|
Fingerprint empowers enterprises to detect and stop online fraud with the world’s most accurate device intelligence. We lead our industry with bleeding-edge identification capabilities and work on turning new ideas and discoveries in the fraud detection space into reality. Our customers range from innovative startups to leading enterprise companies, including Plaid, Dropbox, and Booking.com.
Fingerprint is a globally dispersed, 100% remote company. We were named on on the 2026 Forbes Best Startup Employers list and ranked #803 on the 2026 Inc. 5000 list of America’s fastest-growing private companies.
We have raised $77M and are backed by Craft Ventures (Tesla, Facebook, Airbnb ), Nexus Venture Partners ( Postman, Apollo.io, MinIO, Druva) and Uncorrelated Ventures ( Redis, Rollbar, Gradle).
We are looking for a Senior Web Browser Researcher to push the accuracy and stability of Fingerprint's core identification and fraud-detection products. You'll independently discover, validate, and drive to production new device-identification and bot-detection techniques in modern web browsers — owning findings from first signal through engineering implementation. This role suits someone who thrives on deep, open-ended research into JavaScript, Web APIs, and browser internals, and who cares as much about whether a finding ships and moves the metric as about finding it.
Responsibilities
- Independently research novel device-identification, visitor-identification, Smart Signals, and bot-detection techniques across modern browsers, thriving where requirements are not fully defined.
- Own findings end to end: assess whether a signal is genuinely actionable within real-world constraints (performance budget, execution context, same-site and proxy implications, interaction with existing signals), back the assessment with data, and deliver a clear recommendation with impact estimates (expected false-positive/false-negative rates, expected improvement, limitations, and trade-offs) that product and engineering can act on.
- Stay engaged through implementation — review engineering's changes against the research intent, answer questions as they surface, and advise on edge cases the write-up couldn't fully specify.