Python Engineer

Zama’s mission is to bring end-to-end encryption to AI. Using their homomorphic development framework, companies can process their customer’s data without seeing it, thereby preventing data breaches and surveillance.

Zama’s solution is based on a breakthrough in homomorphic encryption, which enables doing data science and machine learning on encrypted data. Zama is open-source by design, as they believe privacy-enabling technologies should benefit the widest possible community of developers and researchers.

Zama’s cofounders are Dr Pascal Paillier, one of the most renowned cryptography researchers, and Dr Rand Hindi, a serial entrepreneur who formerly founded Snips.

The Homomorphic Development Framework (HDK) team is building an open source framework for homomorphic machine learning. More precisely, we build a set of tools to help our users to do everything needed for having and deploying their fully homomorphic encryption (FHE) network, i.e., to: (i) train neural networks which are FHE-friendly, (ii) compile these networks into FHE networks running over encrypted data, and (iii) deploy those compiled networks.

HDK’s main task is to develop and maintain the ML-specific tools (notably, training or post-training tools). Some of the tools are made by other teams at Zama and it is also one of HDK’s missions to expose them in a clean and unified package. With our tools, the user can develop neural networks which can be used in a context where user privacy is ensured end-to-end, even if executed on an insecure server.

The goal of our tools is to be as user-friendly as possible, while reducing the accuracy of networks as little as possible. Notably, we want to not require the user to understand anything about cryptography, or, said in another way, we want to provide tools which look similar to what data scientists are already using on a day to day basis.

Work in our team is a clever mix between research and product: on one side, we need to deeply understand and even make the research progress in some of the advanced machine learning topics, in order to be able to both have FHE-friendliness and excellent accuracy; on the other side, we need to have a clean, unified and updatable product suite regrouping our tools with tools of the other teams in Zama. We also make sure to follow Zama’s open-source policy.

In HDK, we are looking for an engineer with relevant experience in python (or at least, in C/C++/Rust). Ideally, the candidate would also have experience with ML frameworks (e.g., tensorflow-lite, torch, ONNX). Understanding of cryptography is a plus, but not required.

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

• developing the ML-specific tools, to train or post-train FHE-friendly networks, with the guidance of our ML researchers
• developing the product, mainly in python, in a simple, clear and efficient way
• managing our open source repositories and the community around it

• experience in development of production tools, in python notably
• experience in release and continuous integration (easy installation, containers etc)
• experience in bindings (e.g., Rust or C++)
• knowledge of working with OKRs or under a similar performance management structure
• optionally: experience in deep learning and notably quantization / compression of neural networks is a plus
• optionally: interest in research
• optionally: experience with FHE or cryptography
• 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/