Senior Web Browser Researcher

About this role

Fingerprint is a remote-first company that specialises in device intelligence to detect and stop online fraud. They are hiring a Senior Web Browser Researcher to advance the accuracy and stability of their identification and bot-detection products by researching and turning browser-related findings into production features. The role focuses on deep, open-ended research into JavaScript, Web APIs, and browser internals, with ownership from initial discovery to engineering implementation. The position is suitable for someone who cares about whether findings ship and impact metrics as much as about the discovery itself. The company outlines a global, fully remote team and provides pay transparency with a broad salary range across locations.

What you would do

• Independently research novel device-identification, visitor-identification, Smart Signals, and bot-detection techniques across modern browsers.
• Assess whether a signal is actionable within real-world constraints and back assessments with data, delivering recommendations and impact estimates.
• Engage through implementation, reviewing engineering changes against research intent and advising on edge cases.
• Build and maintain research tooling (observers, fuzzers, scrapers) to surface new signals and detect browser changes automatically.
• Track browser changes ahead of release through beta channels and discussions, translating them into product impact.
• Produce structured research outputs for internal teams and for product and engineering, including proofs of concept and experimental analyses.

What they are asking for

• Deep understanding of web platform fundamentals, browser internals, and web security concepts.
• Strong proficiency in JavaScript and ability to read and navigate multiple programming languages.
• Solid grasp of web networking fundamentals.
• Proven ability to uncover and explain undocumented behavior through testing, debugging, and reverse engineering.
• Track record of driving research from idea to validated, actionable results with experiments on real traffic and data.
• Recognised depth in at least one area (e.g., reverse engineering, network research, or identification) with breadth across adjacent areas.
• Clear communication of findings, impact, and trade-offs to engineering and product partners.

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