AI Engineer

Descripción del trabajo

About the job

In BETWEEN we offer you the opportunities you need to achieve your professional goals. If you want to develop your skills in IT and Engineering, this is your next destination!

We support a wide variety of areas such as Firmware, Software, BI, Design, Project Management, and much more. Additionally, we develop tailor-made technological solutions from our BETWEEN Labs.

We are looking for a AI Engineer, specialized in Cryptographic ML Systems to expand one of our teams in Barcelona.

Functions

As an AI Engineer, you'll contribute to the development of a robust execution layer where AI models can run verifiably and confidentially. This role bridges applied cryptography, secure ML inference, and systems-level programming to build a foundation for trusted AI.

Youll work on technologies like Fully Homomorphic Encryption (FHE), Zero-Knowledge Machine Learning (ZKML), and advanced cryptographic protocols such as zkSNARKsintegrating these into our AI OS. Expect hands-on work in Rust and Python, deep exploration of mathematical and cryptographic constructs, and close collaboration with research, hardware, and runtime teams. Reporting to the Secure AI Optimization Lead, your work will be critical to making secure AI scalable and real-world ready.

Your Responsibilities Will Include, But Are Not Limited To

• Design and implement FHE-based inference pipelines using libraries like Zamas Concrete; assess performance and potential integrations.
• Prototype zero-knowledge proof (ZKP) systems to verify AI model execution using tooling such as Circom, ezkl, Halo2, or zkVM environments.
• Take part in defining and building our clients composable architecture for verifiable and privacy-respecting machine learning.
• Write and optimize Rust and Python libraries to compile, execute, and verify ML models within secure execution contexts.
• Develop APIs and backend services for cryptographic inference and proof generation; contribute to PoC integrations for real-world deployments.
• Interface with compiler and runtime teams to ensure smooth integration of secure ML components into the broader AI OS.
• Evaluate performance and resource trade-offs in deploying cryptographically verified models on custom hardware platforms.
• Contribute to the evolution of future proving systems tailored to the companys secure AI silicon stack.
  
  

• Health insurance with Sanitas
• Opportunities for training: Languages, Certifications, Bootcamps, and much more
• A multitude of events: BETWEEN Night, Padel Tournament, Black Mamba Race, and much more
• Flexible remuneration (restaurant, transportation, childcare)
• Incentives for validating or recommending talent
  
  

• Masters or PhD in Computer Science, Cryptography, Applied Math, or a related technical fieldor equivalent hands-on experience.
• 5+ years of experience in systems programming, with strong proficiency in Rust (preferred) and Python, particularly for performance-sensitive or security-critical applications.
• Direct experience with cryptographic proof systems (e.g., zkSNARKs, STARKs, Halo2) and/or FHE frameworks (such as Concrete, TFHE, SEAL).
• Solid foundation in mathematics or algorithmic design, particularly in areas like constraint systems, polynomial algebra, or lattice-based cryptography.
• Familiar with concepts in secure ML inference, model attestation, and privacy-preserving execution.
• Comfortable debugging at a low level and optimizing systems for compute and memory efficiency.