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 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:
Our project requires developed Python ML packages to be deployed both to our biometric device (the Orb) for testing and production use, as well as to internal servers for development and monitoring.
To make any release of our Python code easily available to various environments, we require the implementation of a robust build and distribution system.
This role is responsible for implementing build and distribution systems for Python packages according to latest best practices.
This involves working with various AI & Biometrics workstreams to align our codebase to a common packaging and distribution standard as well as implementing and maintaining DevOps automations.
This role acts as the intersection between the AI & Biometrics team and the Orb software team to understand and uphold requirements set for our developed Python packages and to make them integrate smoothly with our existing environment on the device.
In this role you will:
- Implement and maintain solutions for distributing Python packages across AI & Biometrics workstreams.
- Interact with the Orb software team to discuss requirements for our ML packages to be deployed on the device.
- Implement automated tests comparing computations between different environments.
- Write automations to generate build artifacts for a number of different use cases.
- Investigate package dependency management
About You:
- Industry experience in developing Python applications and deploying packages in production.
- Expert knowledge in Python language and best practices.
- Experience with Docker and DevOps automations.
- Desire to dig deep into presented problems
- Independent and self-organized working style
- Bonus: Familiarity with deep learning frameworks such as PyTorch