FHE Engineer
Nanyang Technological University + TT-logic, Singapore
TT-logic is a cutting-edge start-up, part of Nanyang Technological University (NTU) in Singapore (through its incubator NTUitive). The company specializes in developing interpretable, compact and verifiable neural network models that can be deployed with privacy-preserving inference. We provide transparent, understandable, and secure AI solutions to clients, leveraging TTnet, a technology developed at NTU.
Job Summary:
Thanks to a recently awarded tech-development grant, we are seeking a talented and motivated Fully Homomorphic Encryption (FHE) Engineer to join our team. Your role will be to implement and optimize TTnet privacy-preserving inference through Zama's Concrete-ML library and other FHE libraries, manage cryptographic parameters, and compilation. You will help finalize prototypes and ship reproducible, containerized, and well-documented packages. You will collaborate with a Machine Learning engineer and our full-stack engineers to integrate your FHE pipeline into deployable privacy-preserving pilots in clients' environments.
This role offers an exciting opportunity to work with cutting-edge technology, shape the future of XAI/privacy-preserving AI, and contribute to the success of a promising startup.
Qualifications:
Contact: Please submit your resume, cover letter, and any relevant supporting documents (links to code/repos welcome) to thomas.peyrin@ntu.edu.sg with the subject line "FHE Engineer - Application". Only shortlisted candidates will be contacted for further steps in the selection process.
Job Summary:
Thanks to a recently awarded tech-development grant, we are seeking a talented and motivated Fully Homomorphic Encryption (FHE) Engineer to join our team. Your role will be to implement and optimize TTnet privacy-preserving inference through Zama's Concrete-ML library and other FHE libraries, manage cryptographic parameters, and compilation. You will help finalize prototypes and ship reproducible, containerized, and well-documented packages. You will collaborate with a Machine Learning engineer and our full-stack engineers to integrate your FHE pipeline into deployable privacy-preserving pilots in clients' environments.
This role offers an exciting opportunity to work with cutting-edge technology, shape the future of XAI/privacy-preserving AI, and contribute to the success of a promising startup.
Qualifications:
- Bachelor, Master or PhD degree in Computer Science, Software Engineering, Cryptography, or a related field.
- Experience with Concrete-ML library from Zama or other FHE/crypto libraries.
- Hands-on Docker and CI/CD experience, comfort with Linux tooling, clear documentation.
- Effective communication and interpersonal skills to collaborate with other engineers.
Last updated: 2025-12-01 posted on 2025-11-21