Worldcoin.org is hiring a
Web3 Machine Learning Infrastructure Engineer

Compensation: $98k - $156k *

Location: remote

About the Team:

The AI & Biometrics team is building a state-of-the-art iris recognition engine that works on the 1B+ people scale. In order to do this, we use a fusion of custom optics, hardware, and on-device machine learning, combined with large-scale data collection in more than 20 countries to amass over several million images monthly. These images need to be pre-processed and passed through both external and in-house labelling services.

About the Opportunity:

From field tests all over the world we receive data from various demographics to train our ML models. These images need to be pre-processed and passed through our labelling services before they can be used for training neural networks. This role is responsible for building, scaling, and maintaining a stable data pipeline.

In this role you will:

  • Design data pipelines to handle large scale data ingest. This includes figuring out ways to store and process this data with robust features for filtering, pre-processing, and versioning.
  • Build out data infrastructure to train large neural networks using self-supervised and contrastive learning.
  • Build and refine custom data labeling services that directly influence the quality of our iris recognition engine.
  • Work closely with other internal stakeholders to incorporate their data usage needs.

About You:

  • Have industry experience as a Data Engineer, Machine Learning Engineer, or Data Scientist, dealing with data infrastructure, distributed systems, and fault tolerant data pipelines.
  • Experience deploying models and infrastructure on Kubernetes.
  • Experience with infrastructure tools for provisioning, deployment, and monitoring such as Terraform, AWS, Docker, and Datadog.
  • Experience with heterogeneous data sources and data models including MongoDB, PostgreSQL, Redis, and Neo4J.
  • Own problems end-to-end, and are willing to pick up whatever context is needed.
  • You enjoy working as part of a fast-moving team, where perfectionism can sometimes be at odds with pragmatism.
  • A desire to dig into problems across the stack, whether networking issues, performance bottlenecks, memory leaks, or simply reading unfamiliar code to figure out where potential issues might exist.
  • Have a strong belief in the crucial need of high-quality data for producing state of the art machine learning systems.

#LI-Remote

Apply Now:

This job is closed

Compensation: $98k - $156k *

Location: remote

This job is closed


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