Founding Device Fingerprinting Engineer
Remote ✓About Prelude Prelude is redefining how companies authenticate and onboard users - turning what's traditionally a cost center into a growth lever. Our flagship product lets businesses send OTP codes with the best price-to-conversion ratio on the market, dynamically selecting the most effective channel in real time (optimized SMS, WhatsApp, and more) while actively blocking spam and fraud that legacy providers miss. Founded in 2022 by former Zenly team members who lived the pain of broken SMS authentication firsthand, we're already serving fast-growing companies across Europe and are expanding into the US. But authentication is only the starting point - we're building the platform for trust at scale, with an ambitious roadmap of market-defining products ahead. Why join us Today, we're a team of 60 and growing, based in Paris, building products that power secure and high-performance user onboarding for companies across the world. We believe small, highly skilled teams outperform large, fragmented organizations, and we are intentional about staying focused on impact, quality, and speed. We operate with a flat org structure and value in-person collaboration, which helps ideas move faster, decisions stay grounded, and teams take full ownership of what they build. Our values • Care We care deeply about our customers, our teammates, and the quality and reliability of what we ship. • Bias for Action We move fast, test in the real world, and iterate quickly rather than over-optimizing in theory. • Ownership We take responsibility end to end, from identifying problems to delivering outcomes and learning from results. ABOUT THE ROLE Fingerprinting is becoming a first-class pillar of Prelude's fraud detection engine — and this is the founding role that will define it. You will own the entire fingerprinting surface: architecture, research, production systems, and eventually the team we build around you. You'll report directly to leadership and shape the roadmap from scratch. Fraud is an adversarial game. Attackers use emulators, residential proxies, VPNs, device spoofing, and anti-detect tooling to flood our customers' authentication pipelines with fake traffic. Your job is to make that invisible — or at least expensive enough not to be worth it. You'll build the systems that collect, process, and exploit device and network signals at scale: from raw hardware attributes and TLS fingerprints to IP risk scoring and carrier intelligence. You'll combine classical feature engineering with ML to produce high-fidelity risk signals that feed our real-time scoring engine — processing millions of authentication attempts per day in milliseconds. This role sits at the intersection of security research, systems engineering, and applied machine learning. It's for someone who thinks like an attacker, builds like an engineer, and reasons like a data scientist. WHAT YOU'LL BE DOING: • Owning the fingerprinting roadmap end to end — from signal collection in our mobile SDKs (iOS, Android) and server-side APIs, to the feature engineering pipelines that turn raw attributes into fraud signals • Building and hardening device fingerprinting systems — persistent device identity across app reinstalls, rooted/emulated device detection, hardware attestation, and spoofing resistance for both web and mobile contexts • Developing network intelligence signals — IP reputation scoring, proxy/VPN/datacenter detection, TLS/JA4 fingerprinting, carrier and MCCMNC enrichment, and residential vs. commercial traffic classification • Applying ML to fingerprinting problems — anomaly detection on device attribute distributions, clustering to identify fraud rings sharing infrastructure, supervised classification of suspicious signal patterns, and adversarial robustness against evolving evasion techniques • Integrating with our real-time scoring engine — producing low-latency features that enrich our per-authentication risk model under strict latency constraints • Researching attacker techniques — reverse-engineering anti-detect tooling, automation frameworks, and bypass techniques to stay ahead of the adversarial curve • Laying the groundwork for a team — defining engineering standards, research practices, and data pipelines that will scale as we hire around you. WHAT WE'RE LOOKING FOR: • 5+ years of experience in a relevant field — fraud detection, bot mitigation, mobile security, or detection engineering; you've shipped systems in production, not just research prototypes • Deep knowledge of device fingerprinting — mobile hardware signals, OS-level attestation (Play Integrity, DeviceCheck, SafetyNet), browser fingerprinting APIs, and spoofing/emulation detection • Hands-on experience with network intelligence — TLS fingerprinting (JA3/JA4), IP enrichment pipelines, proxy/VPN classification, AS number analysis, and carrier-level signals • Applied ML experience in a security context — feature …
