Founding Device Fingerprinting Engineer

Stack

Responsibilities

• ▹Own the fingerprinting roadmap end to end, from signal collection in mobile SDKs (iOS, Android) and server-side APIs to the feature engineering pipelines that turn raw attributes into fraud signals
• ▹Build and harden device fingerprinting systems: persistent device identity across app reinstalls, rooted/emulated device detection, hardware attestation and spoofing resistance for web and mobile
• ▹Develop network intelligence signals: IP reputation scoring, proxy/VPN/datacenter detection, TLS/JA4 fingerprinting, carrier and MCCMNC enrichment and residential vs. commercial traffic classification
• ▹Apply 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
• ▹Integrate with the real-time scoring engine, producing low-latency features for the per-authentication risk model under strict latency constraints
• ▹Research attacker techniques: reverse-engineer anti-detect tooling, automation frameworks and bypass techniques to stay ahead of the adversarial curve
• ▹Lay the groundwork for a team: define engineering standards, research practices and data pipelines that will scale as the team grows

Requirements

• ▹5+ years of experience in a relevant field (fraud detection, bot mitigation, mobile security or detection engineering); 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 engineering, anomaly detection, clustering and classification with end-to-end ownership from training through production deployment
• ▹An adversarial mindset: knowledge of the attacker landscape (emulators, spoofing techniques, anti-detect browsers, residential proxy networks) and designing systems with bypass attempts in mind
• ▹A preference for simple, robust designs over clever, fragile ones, with strong intuition for what will hold up at scale under active adversarial pressure
• ▹Fluent English, given the international team and customer base

Nice to have

• ▹Familiarity with phone/SIM authentication context, GSMA intelligence or telco APIs
• ▹Experience with JA4 or other network fingerprinting techniques
• ▹Proficiency in Go, Rust or Python for backend/data work
• ▹Experience with stream processing systems (SQS, Kafka) or OLAP stacks (ClickHouse, Redshift)
• ▹iOS or Android SDK internals knowledge
• ▹Published research, open-source contributions or technical writing in the fraud/bot detection space

Soft skills

What we offer

• ▹Competitive compensation package with BSPCEs
• ▹Flexible remote policy
• ▹100% of travel to the office subsidised
• ▹Health insurance via Alan
• ▹Urban Sports Club gym membership
• ▹Laptop and a phone (for on-call rotations)
• ▹Swile meal vouchers
• ▹Free snacks and drinks in the office
• ▹Annual offsite in a great location
• ▹The opportunity to build something from 0-1 and make an impact every day

About the company

Prelude is redefining how companies authenticate and onboard users: its flagship product sends OTP codes with the best price-to-conversion ratio on the market, dynamically selecting the best channel in real time (SMS, WhatsApp and more) while blocking spam and fraud that legacy providers miss. Founded in 2022 by former Zenly team members, the Paris-based team of about 60 already serves fast-growing companies across Europe and is expanding into the US.