Senior Machine Learning Engineer, Presentation Attack Detection

About the Company:
World is a network of real humans, built on privacy-preserving proof-of-human technology, and powered by a globally inclusive financial network that enables the free flow of digital assets for all. It is built to connect, empower, and be owned by everyone.This opportunity will be with Tools for Humanity.
About the AI & Biometrics Team:
The AI & Biometrics team is building a biometric iris recognition system that can work reliably with more than a billion users to assess humanness online. This is the key to ensure account uniqueness and authenticity for Worldcoin and its downstream applications like the WLD token distribution, online governance, etc. We use cutting-edge machine learning models deployed on custom hardware to enable high-quality image acquisition, identification, and fraud prevention, all while requiring minimal user interaction.
We are building an iris recognition and fraud detection engine that works on the 1bn people scale. Therefore, its performance needs to out-perform all the current iris recognition technologies. We leverage our powerful custom-made iris recognition and presentation attack detection device, the Orb, combined with the latest research from the field of AI and Deep Learning.
 
About the Opportunity:
As Worldcoin’s user base keeps growing, so does the quantity and diversity of fraud attempts. Your role as a Senior MLE in the AI & Biometrics team will be to train, deploy and improve models for Spoof and Presentation Attack Detection. Your models will run on our custom hardware, the Orb, as well as mobile platforms such as the World App.
In this role you will:

Take ownership of, and develop deep learning models and classical algorithms that run on deployed or mobile hardware
Build and maintain deep learning model training pipelines
Drive the entire model value chain, from guiding our internal data collection team, to building, deploying, monitoring and improving models

 
About You:

4+ years of industry experience in Computer Vision, Deep Learning and / or Data Science.
Experience in training, deploying and iterating over deep learning models that impacted large userbases in a production environment
M.S. in Computer Science, Data Science, or other STEM major
Strong programming skills in Python including the usual data science and computer vision libraries: open-cv, pandas, numpy, seaborn, etc.
Strong experience with a deep learning framework, ideally PyTorch and its ecosystem
Excellent communication skills, including fluent english
Thrive in high-paced environment, able to perform outstanding work in short timelines
Experience using cloud-based platforms and tools (e.g., AWS, GCP, Azure) and NoSQL databases (e.g. MongoDB, ElasticSearch, Redis, etc.

Nice to Have:

Experience training Deepfake detection, Presentation Attack Detection, or vision-based fraud detection models
Experience training, deploying and maintaining models on embedded hardware
Experience or knowledge of Rust

 
What we offer:

An open and collaborative office space  
Unlimited PTO  
Monthly Phone Reimbursement or a company device
Daily in-office meals 
Top-tier medical, dental, vision insurance 
Retirement or pension program

 
The reasonably estimated salary for this role at TFH in Munich ranges from €124,000 - €164,000, plus a competitive long term incentive package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience.