The product your team will design, develop, test and maintain aims to take any DAG (directed acyclic graph) —- or later, any program —- and to transform it into a fully homomorphic equivalent, with tunable and small accuracy loss. Notably, a first usage will be to convert neural networks into end-to-end encrypted equivalent programs, which can virtually run on an insecure server while maintaining user’s privacy. In this manner, the product has strong relations with compilers or code-to-code translators. Challenges are about having good performance, small accuracy loss and no compromise on security at the same time.

Your team (and thus you) will be responsible for:

• turning any program in a fully homomorphic equivalent (with the help of our crypto research team)
• finding the best parameters following the constraints, to optimize speed, RAM & data size, while maintaining security
• developping the product in a clear & efficient way, mainly in python
• making the use of our compiler as easy to use as possible for our users
• publishing or blog the techniques used by the tool
• managing our open source repositories and the community around it

• experience implementing compilers, optimization passes, operational analysis or code-to-code translator
• development of production tools in python or C/C++/Rust
• optionally: experience with FHE or cryptography
• optionally: experience with deep learning
• be passionate about privacy and open source

Our process is described in detail here: https://zama.ai/2020/04/28/how-we-hire-at-zama/