Senior Machine Learning Engineer (Biometrics & Face Recognition)
Hardturmstrasse 181, 8005 Zürich · Software / Computer Vision · Aktiengesellschaft · Englisch
Wer wir sind
Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows. It provides actionable insights to help businesses in a variety of industries. Join us as we continue to expand, grow, innovate, and help take Scandit to the next level.
What you will do
Design, train and evaluate models for face detection, face recognition and 1:1 face matching against ID document portraits Support the team's work on liveness and presentation attack detection (PAD) against spoofs, replays and deepfakes Define quality metrics, benchmarks and test sets that meet high-assurance and regulatory expectations Own the full loop: data collection and labelling strategy, prototyping, training, evaluation, debugging and model integration Optimise models for on-device inference with our C++ engineers (quantisation, pruning, mobile runtimes) Track research in biometrics and face anti-spoofing, and turn it into product direction Mentor engineers on ML practice
Who you are
We are looking for an experienced ML engineer who has shipped production models to real users and has worked hands-on with biometrics. You are comfortable owning ambiguous problems, moving fast and then iterating. You also work well with product, C++ and QA engineers. 5+ years as an ML engineer, with production models shipped to real users Hands-on experience with biometrics: face recognition, face verification, liveness or PAD Fluent in Python and at least one deep learning framework (PyTorch preferred) Strong grasp of evaluation for security-sensitive systems: FAR/FRR, bias and fairness across demographics, adversarial robustness Clear communicator who works well across disciplines Eligible to work in the hiring location Knowledge of standards such as ISO/IEC 30107 (PAD), NIST FRTE/FATE or iBeta testing Experience deploying models on mobile or edge (TFLite, ONNX Runtime, Core ML) Working knowledge of C++
Fähigkeiten
Python
C++
ML / AI
PyTorchMachine LearningGehaltsspanne
Auf AnfrageDieser Arbeitgeber nennt die Gehaltsspanne im ersten Gespräch.
Kontakt
All qualified applicants will receive consideration for employment without regard to race, color, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.
