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About the Team: The AI & Biometrics team is building a biometric iris recognition system that can work reliably with ...

Data Science Scientist Remote Tensorflow

$45k - $75k* · Senior Fully remote

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About the AI & Biometrics Team: The AI & Biometrics team is building a biometric iris recognition system that can wor...

Dev Machine Learning Remote Engineer

$98k - $156k* · Senior Fully remote

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Data Scientist

Worldcoin.org remote

$45k - $75k Senior Full-time

About the Team:

The AI & Biometrics team is building a biometric iris recognition system that can work reliably with more than a billion users and enables them to claim their free share of WLD. We use cutting-edge machine learning deployed on custom hardware to enable high-quality image acquisition, identification, and fraud prevention, all while requiring minimal user interaction. Our technology, coupled with privacy-preserving data collection, allows us to increase system performance and reduce model bias.

About the Opportunity:

Building an identification engine on Worldcoin’s scale requires a deep understanding of our data. Through dedicated field tests we receive data that is forwarded into our knowledge graph. This graph is not only used to generate datasets for downstream consumption in ML models, but can also be leveraged to detect fraud and much more. This role is responsible for developing the knowledge graph, generating insights, and creating large high-quality datasets to train various ML models.

In this role you will:

Apply various machine learning algorithms to raw image data in order to create and validate biometric datasets. This might include: face recognition using neural networks, traditional iris recognition using Gabor wavelets, etc.
Analyze patterns in metadata to detect inconsistencies and find fraud cases.
Implement new field tests with our distribution and data collection teams to create larger datasets.
Build and refine custom data labeling services that directly influence the quality of our iris recognition engine.
Work closely with other stakeholders (data contributors + consumers) to incorporate their data usage needs on a variety of tasks and domains.

About You:

Fluent in Python with past experience with computer vision, machine learning, and deep learning (Tensorflow/Pytorch).
Solid background in math and statistics, with experience translating research results into working products.
Ability to read and understand scientific papers, reproduce results, and transfer techniques to other domains
Bonus: Experience interacting with MongoDB, AWS, and related cloud infrastructure.

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