Intelligent Edge Engineer
$135,000–$155,000 year
RemoteUnited States
Job Summary
Design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. Execute model compression, quantization, and pruning techniques while leveraging strong systems engineering skills to ship reliable AI capabilities outside the data center. Manage compute, memory, energy, and connectivity constraints to shape engineering trade-offs in production environments. Requires 6+ years of ML engineering experience with proficiency in Python and C++. Full-time, direct W2 role at $135,000–$155,000 annually for U.S. citizens and transfer candidates.
Required Qualifications
- 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.
Desired Qualifications
- 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.
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