Design and implement security solutions for customer-provided ML models running on embedded hardware using secure execution environments and enclaves.
Develop secure boot and firmware integrity mechanisms for AI-enabled embedded platforms.
Implement runtime hardening and isolation for ML workloads.
Enable model protection using Trusted Execution Environments (TEE) and secure enclaves.
Ensure secure loading and execution of ML models (ONNX, TensorFlow Lite) on edge devices.

Have a background in Computer Science, Cybersecurity, or Cryptography and a strong interest in applied ML, OR
Have a background in Machine Learning and an interest in cybersecurity.
5 years of more experiences in embedded programming (C/C++, Rust).
Understanding of secure boot, firmware integrity, and runtime security.
Experience with or interest in TEEs, TPM integration, and secure enclaves.
Familiarity with ML model formats and deployment workflows.
Knowledge of cryptographic primitives for integrity and confidentiality.

Senior Embedded AI Platform Security Engineer

Key skills