pFull-time | On-site with flexibility /ppAt Global ID, we develop finger-vein biometric identification systems, combining our own near-infrared scanners, matching algorithms and identity platform, deployed on-premises in real-world environments, including public-health programmes. /ppWe are looking for a Senior Biometrics Engineer to take ownership of our entire biometric pipeline, from image quality assessment to large-scale identification. /ppYou will improve our existing algorithms, lead the development of their successors, build robust evaluation methods and ensure reliable integration into our production platform. /ppThis is a hands‑on senior role with genuine technical ownership, working closely with our scanner engineer, platform team, field operations in Kenya and academic research partners. /pulliOwn the biometric algorithm roadmap: improve our current C++/OpenCV matcher and lead the development of future versions. /liliLead biometric evaluation: design rigorous protocols covering FMR/FNMR, DET curves, FPIR/FNIR, confidence bounds and cross-device or cross-session analysis. /liliBuild and manage datasets: define collection protocols, quality controls, labelling, consent requirements and data-protection safeguards. /liliImprove end‑to‑end accuracy: work on image quality, capture feedback, image enhancement, feature extraction, learned matchers, two‑finger score fusion and threshold calibration. /liliDesign safe algorithm transitions: implement versioned templates and parallel matcher versions, enabling enrolled users to migrate progressively without disrupting existing deployments. /liliIntegrate algorithms into the product: collaborate on matcher services, APIs, Java/Python services, containers and release packaging. /liliDrive performance and scalability: optimise processing times, memory usage and CPU performance, and develop search strategies for 1:N identification at scale. /liliLead research collaborations: define data formats, evaluate research deliverables and integrate promising results into the product. /liliDocument and share knowledge: produce evaluation reports, technical decision records and onboarding material. /li /ululliApplied biometrics or computer vision experience: several years working on systems used in real‑world applications. Around five years or more is a useful benchmark, but practical achievements matter most. /liliStrong biometric evaluation skills: understanding of operating points, verification versus identification, false‑match risks and statistical confidence. /liliPython and machine learning: strong Python skills for data analysis and model training, using PyTorch or an equivalent framework. /liliC++ and image processing: ability to read, profile and modify image‑processing code, particularly with OpenCV. /liliReal‑world dataset expertise: experience with imperfect datasets, augmentation, cross‑validation, leakage prevention and device/session variability. /liliProduction software engineering: experience with Java or Python back ends, REST APIs, Docker, testing and performance optimisation. /liliReproducible engineering practices: version control, containers, measurable improvements and reproducible pipelines. /liliAutonomy and communication: ability to make technical decisions, document them clearly and flag issues early. /liliLanguages: professional English. French is an advantage, but not required. /liliWork authorisation: right to work in Switzerland or eligibility to obtain it. /liliExperience with vascular biometrics, particularly finger‑vein or palm‑vein recognition, or other near‑infrared imaging technologies. /liliExperience with large‑scale identification systems, embeddings, approximate search, indexing, distributed matching or GPU inference. /liliKnowledge of presentation attack detection, biometric template protection (ISO/IEC 24745), biometric standards or certification. /liliExperience deploying technology in low‑resource environments, including public‑health programmes in emerging markets. /liliExperience translating academic research into production‑ready solutions. /liliFamiliarity with modern AI‑assisted development tools. /liliReal‑world impact: your measurements and decisions can influence field deployments within months. /liliFull technical ownership: take responsibility for the biometric development line in a small, collaborative team. /liliTechnology in action: contribute to systems already in use, including public‑health pilots. /liliHardware and software under one roof: work directly with our scanner engineers to improve image capture at its source. /liliResearch‑driven environment: join us at EPFL Innovation Park, close to the academic and scientific community. /li /ulpWe would love to hear from you. /p #J-18808-Ljbffr
