ZK & Machine Learning Compiler Developer

About the Role

A forward-thinking research and development team is seeking a Compiler Developer specializing in Zero-Knowledge Proofs (ZKPs) and Machine Learning (ML). This role sits at the crossroads of cryptographic algorithms, compiler optimization, and AI-powered computation, offering a unique opportunity to contribute to cutting-edge advancements in privacy-preserving machine learning.

As a key contributor, you will be responsible for designing and implementing high-performance compilers that bridge the gap between ML models and ZK execution frameworks. This position demands expertise in cryptographic engineering, compiler design, and systems architecture to drive innovation in privacy-focused computing.

Key Responsibilities

• Architect and develop compilation pipelines that translate ML computations into Zero-Knowledge-friendly formats.
• Optimize cryptographic primitives and proof-generation techniques for enhanced efficiency and scalability.
• Work closely with cryptographers and ML researchers to refine zkML integration within decentralized frameworks.
• Design compiler backends that interface with high-performance cryptographic proving systems.
• Conduct rigorous benchmarking to ensure optimized execution of ML inference within Zero-Knowledge circuits.
• Contribute to open-source research and actively engage with developer communities in the ZK and ML space.

Required Skills & Qualifications

• Strong proficiency in compiler development, optimization, and systems programming.
• In-depth understanding of Zero-Knowledge Proofs, cryptographic protocols, and constraint systems.
• Experience in ML model representation, quantization, and efficient inference techniques.
• Proficiency in Rust, C++, or LLVM-based compiler toolchains.
• Familiarity with zk-SNARKs, zk-STARKs, or other cryptographic proving systems.
• Ability to work with low-level system architectures to optimize computational efficiency.
• Prior contributions to research-driven projects or open-source cryptographic initiatives.

Preferred Qualifications

• Hands-on experience with zkML frameworks, such as EZKL or similar cryptographic ML compilers.
• Understanding of secure multi-party computation (MPC) and homomorphic encryption (FHE).
• Background in formal methods and verifiable computation.
• Track record of research publications or contributions in ZK, cryptography, or ML systems.

Why Join Us?

• Work at the forefront of privacy-preserving AI and cryptographic research.
• Join a global team pushing the boundaries of Zero-Knowledge applications in ML.
• Competitive compensation and opportunities for cutting-edge innovation.
• Remote-friendly work environment with flexibility and autonomy.
• If you’re passionate about secure computation, compiler engineering, and ZK-powered AI, let’s build the future together.

Darwin Recruitment is acting as an Employment Agency in relation to this vacancy.

Reece Waldon