Role OverviewDesign, optimize, and deploy machine learning models for edge devices, requiring expertise in model compression, quantization, and hardware-aware optimization.
What You Will Do
Key responsibilities include designing edge AI solutions, applying quantization and pruning techniques, tuning model performance, building inference runtimes, and implementing on-device model update workflows.
Why It Might Be a Fit
The ideal candidate has shipped edge AI in production environments and has strong systems engineering skills to ship reliable AI capabilities outside the data center.
Requirements
- 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.
Benefits
- Salary range: $100,000–$155,000 Annually
- 100% Remote work arrangement
- Full-time, Direct W2 position
- U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates encouraged to apply
- Equal Opportunity Employer
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