Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
Six or more years of experience in ML engineering, with significant work on edge or mobile AI.
Strong proficiency in Python and C++.
Hands-on experience with model compression, quantization, and pruning techniques.
Experience with at least one major edge inference framework.
Solid understanding of mobile and embedded hardware architectures.
Experience deploying ML models to production on mobile or embedded platforms.
Strong performance engineering and profiling skills.
Familiarity with on-device privacy and security considerations.
Strong communication and cross-functional collaboration skills.
Experience with custom NPU or DSP toolchains.
Familiarity with federated learning or on-device personalization.
Exposure to safety-critical or industrial edge deployments.
Open-source contributions to edge AI frameworks.
Experience optimizing LLMs for on-device inference.

Edge Computing AI Engineer

Summary