Edge ML Embedded Engineer

Job Summary

Seeking a specialized Edge ML Embedded Engineer for a remote contract position, this role focuses on assessing edge hardware requirements, evaluating inference frameworks, and building a feasibility demonstrator for on-device machine learning applications.

Key Responsibilities

• Assess target edge hardware for on-device inference requirements and evaluate candidate edge runtimes
• Evaluate edge inference frameworks for CPU-only deployment, analyzing quantization approaches and latency
• Design and build a constrained feasibility demonstrator using simulated data feeds to validate architectural approaches

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience
• 5+ years of hands-on experience in embedded systems engineering or edge computing with constrained hardware
• Expert proficiency with at least one edge ML inference framework, such as TensorFlow Lite or ONNX Runtime
• Strong understanding of memory management and real-time data stream handling in resource-constrained environments
• Experience with embedded Linux or similar OS environments, including ARM-based processors