Device Fingerprinting Engineer
Castle
WorldwideremotePosted 29 days ago
Skill Required
Device-Fingerprinting-EngineerSecurity-EngineerFraud-Detection-EngineerBackend-EngineerTrust-and-Safety-EngineerMobile-Device-EngineerAuthentication-EngineerDevice-Management-EngineerJavaScriptData StructuresdesigningbuildingdesignRustAPIsandFulltime
Key highlights
- US-level salaries globally
- Remote-friendly in Europe
- Must have built/operated fingerprinting systems at scale
Role overview
Castle is a small, profitable team building a real-time trust layer for modern platforms, with device fingerprinting as a core component. This role owns the end-to-end fingerprinting system, from browser signal collection to server-side matching logic, addressing challenges like evolving signals, adversarial manipulation, and long-term reliability. The goal is to treat fingerprints as evolving representations to reliably recognize devices over time, even under noisy or adversarial conditions.
Responsibilities
- Own fingerprinting end to end: from signal collection in the browser to the matching logic on the server side
- Work with other JavaScript researchers and detection engineers to design new signals
- Build reliable client-side collection mechanisms
- Develop algorithms that determine whether two fingerprints likely belong to the same device or user
- Design and improve the overall fingerprinting system, from signal collection to matching logic
- Propose new approaches to measure fingerprint quality, stability, and long-term effectiveness
- Detect manipulated or inconsistent fingerprints in adversarial browser environments
- Build matching algorithms that remain reliable despite drift, collisions, and partial fingerprints
- Ensure the system remains performant and resilient as browsers evolve and attacker techniques change
- Take existing production fingerprinting systems much further
Requirements
- Has already built or operated device fingerprinting systems at real scale
- Has worked on signal collection in real browsers, not just theoretical models
- Has dealt with unstable signals, fingerprint collisions, and manipulated environments
- Understands the tradeoffs between entropy, stability, and collection cost
- Has experience designing matching or clustering algorithms that operate under noisy and adversarial conditions
Nice to have
- Has spent time thinking about how to reliably track devices on the modern web — even when the device tries not to be tracked
Benefits
- US-level salaries globally
- Remote-friendly in Europe
Additional details
- Device fingerprinting is often misunderstood; production-grade systems require more than hashing JavaScript attributes
- Browsers and operating systems evolve constantly, with APIs changing or disappearing, and hardware configurations shifting
- Fraudsters actively manipulate environments using anti-detect browsers, patched Chromium builds, canvas manipulation, residential proxies, storage clearing, and identity rotation
- Castle treats fingerprints as evolving representations rather than static identifiers
- The team cares far more about outcomes than hours